Forthcoming and Online First Articles

International Journal of Electronic Security and Digital Forensics

International Journal of Electronic Security and Digital Forensics (IJESDF)

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International Journal of Electronic Security and Digital Forensics (51 papers in press)

Regular Issues

  • Security and Privacy of Adolescents in Social Applications and Networks: Legal Practice of Developing Countries   Order a copy of this article
    by Ahmad Ghandour, Viktor Shestak, Konstantin Sokolovskiy 
    Abstract: The article aims to study the developed countries experience on the legal regulation of cyberbullying among adolescents, to identify existing shortcomings in the developing countries laws, and to develop recommendations for improving the regulatory framework. To do this, the authors have studied the state regulatory practice of the UK, USA, Canada, Malaysia, South Africa and Turkey and analysed the statistics of 2018 on the manifestation of cyberbullying among adolescents in these countries. It turns out that in the countries under review there is either no separate. The percentage of cyber aggression cases among adolescents in developing countries is higher than in developed countries. For example, in South Africa, it is 85%, and in Canada 33%. The results of this study can encourage countries to create separate cyberbullying legislation if they do not have it yet and periodically review and modify already existing legislation.
    Keywords: adolescent protection; cyberbullying; depression; regulations; social networks; suicide.
    DOI: 10.1504/IJESDF.2022.10036942
     
  • Safe and Secure (SaS): An Automated Library Management System for Monitoring Book Rotation using Face Recognition   Order a copy of this article
    by Irfan Ali Kandhro, Fayyaz Ali, Asif Ali Wagan, Iqra Tabassum M, Farhan Afzal 
    Abstract: The automated safe and secure library management system have proposed using human face recognition for monitoring library activities. The manual monitoring task very difficult and the devices are gaining more importance as the amount of its clients is developing. The automated process reduces the manual efforts and duplication work, and saved energy and time and brings the accurate results. The linear binary pattern histogram (LBPH)system works with face detection and recognition for helping to record the information of end users and consumers. The end-consumers of the software are librarians, students, and teachers. With the help of application, the books get issued to the end-consumer through figuring out the consumer with the assist of face recognition. The system captures the face of the consumer and additionally checks the information of the consumer.
    Keywords: Safe and Secure System; Face recognition; computerized / automated library management; information factors; security factors; artificial intelligence; security level.
    DOI: 10.1504/IJESDF.2023.10049565
     
  • Policing Perspective on Pre-emptive and Probative Value of CCTV Architecture in Security of Smart City- Gandhinagar, Gujarat, India   Order a copy of this article
    by Surbhi Mathur, Krittika Sood 
    Abstract: Closed circuit television system is the set of hardware and software combined to record the videos, transmit the recorded signals to the video management system and monitor the footages with the intention of providing protection and surveillance. CCTV is now known to be an important part of every person’s life, whether at home, office or the roads connecting them. Therefore, it is necessary to analyse the present scenario of the working of CCTV and suggesting effective changes that can be implemented for the successful and more impactful outcomes from it. The targeted experimented group included the individuals employed for the CCTV monitoring and handling, in one of the cities of Gujarat. The survey using a questionnaire was conducted, which gave an explicit result about the effectiveness of CCTV towards the prevention, detection and investigation of crimes along with the current scenario about the awareness of the CCTV and its working among individuals marked as subjects in the current study. The study was funded by the National Forensic Sciences University in collaboration with Bureau of Research and Development in order to gauge and assess the value of CCTV architecture in the security of the smart city.
    Keywords: closed circuit television; CCTV; camera; crime; prevention; detection; investigation; awareness; security; privacy.
    DOI: 10.1504/IJESDF.2023.10049566
     
  • A Platform Independent and Forensically Sound Method to Extract WhatsApp Data from Mobile Phones   Order a copy of this article
    by Aritro Sengupta, AMIT SINGH, B.M. Vinjit 
    Abstract: With the increasing usage of WhatsApp worldwide, for text and media communication, WhatsApp data artefacts are prioritised by forensic investigators and LEAs to examine and prosecute crimes. Nowadays, the well-known conventional methods of extraction are failing to extract the required WhatsApp data due to updated security patches of the operating system and various other hardware updates. Investigation may end up to be intangible due to lack of production of WhatsApp data as evidence before the court of law. In this paper, a forensically sound method of extracting WhatsApp data is discussed which works irrespective of the hardware and software specifications of the mobile phone. Several parameters which detect the efficiency of WhatsApp data extraction have been discussed which are based on state-of-the-art technologies and recent field experience. In the later section, we have compared the proposed method with the other conventional methods of extraction.
    Keywords: digital forensic technique; digital forensic tool; mobile forensics; WhatsApp forensics; law enforcement agency; chat crawling; court of law.
    DOI: 10.1504/IJESDF.2023.10050124
     
  • An Experimental Approach for Locating WhatsApp Digital Forensics Artifacts on Windows 10 and the Cloud   Order a copy of this article
    by Yaman Salem, Majdi Owda, Amani Owda 
    Abstract: The increased popularity of WhatsApp resulted to be vastly used as a tool in planning unlawful activities. To conduct WhatsApp investigation, the artifact should be located well. This poses challenges to digital forensic investigators. This study investigates WhatsApp artifacts on Windows volatile and non-volatile memories. WhatsApp desktop and WhatsApp web were analyzed. A set of four experiments conducted. Experiment 1 investigates WhatsApp web artifacts via the cloud, experiment 2 investigates WhatsApp web artifacts on non-volatile memory, experiment 3 investigates WhatsApp desktop artifacts on non-volatile memory, and experiment 4 investigates WhatsApp web/desktop artifacts on volatile memory. Results demonstrated that all related artifacts recovered from the WhatsApp web via the cloud. Moreover, a log file contains user’s activities, contact numbers, and browser history, recovered from non-volatile memory. Messages in clear text and part of images recovered from volatile memory. This study provided a holistic approach for locating and analyzing WhatsApp artifacts.
    Keywords: instant messaging; IM; WhatsApp artefacts; WAA; non-volatile; volatile; Windows.
    DOI: 10.1504/IJESDF.2023.10051774
     
  • A Novel Comparison of Data Analytics and Business Intelligence Tools: A Information Preservation and Ledger Management Solution   Order a copy of this article
    by Danella Patrick, Abdullah Ayub Khan, Fayyaz Ali, Irfan Ali Kandhro, Mahnoor Anwar, Asadullah Kehar, Anwar Ali Sanjrani 
    Abstract: This paper presents the comparison of data analytics, especially in business intelligence tools. A comparative analysis report is based on five data analytics/bi-tools that are mostly used in Pakistan, including tableau, Power BI, Zoho. This proposed analysis strategy provides an overview of how the tools behave/respond concerning their functionalities or domains, including data ingestion/data absorbing, data preparation and data cleaning, data modelling and transforming, data visualisation, data alerts, and data search. 2022 is bringing a lot of evaluation in the companies that work with a large amount of data from scrapping/ingesting to finding insights or outliers. Whereas the main goal is to predict data fluctuations. Finding the right data analytics tool to find the insights and outliers according to the business need is the desire of every business analyst. The proposed report helps a enterprises to move their manual work to an automated data analytics tool.
    Keywords: data analytics; data modelling and transforming; data visualisation; Qlik; tableau; Zoho; ELK stack.
    DOI: 10.1504/IJESDF.2023.10052136
     
  • Susceptibility of Pediatric Pneumonia Detection Model under Projected Gradient Descent Adversarial Attacks   Order a copy of this article
    by Raheel Siddiqi, Syeda Nazia Ashraf, Irfan Ali Kandhro 
    Abstract: Pneumonia is the leading cause of pediatric deaths worldwide. Timely diagnosis can help save a child’s life, long-term health, etc. Chest X-ray (CXR) examination is an effective and economical means to diagnose pneumonia. However, there is lack of expert radiologists in many resource constrained areas. Deep learning based pneumonia diagnosis is a solution to this problem but deep learning models are susceptible to adversarial attacks. This research study investigates the susceptibility of a pediatric pneumonia detection model under projected gradient descent (PGD) attack. Experimental results show that the diagnostic performance of the model degrades sharply when the magnitude of the perturbation, i.e.,ε, is increased from 0.0001 to 0.009 but after that the performance remains almost stable and does not significantly degrade further. The lowest model accuracy attained under the attack is 33.33%. It has been shown that the attack is much more detrimental to the specificity of the model than its sensitivity. Moreover, it has also been demonstrated that the model’s performance can be degraded to unacceptable levels while keeping the perturbations imperceptible.
    Keywords: security; projected gradient descent; adversarial attack; pediatric pneumonia; chest x-ray; CXR; deep learning.
    DOI: 10.1504/IJESDF.2023.10052172
     
  • RecomAlly: Dynamic Ally Recommendation on Twitter based on Rhetorical Structure Theory and Valence Shifters   Order a copy of this article
    by Sai Charan A, Vegesna S. M. Srinivasavarma, Rajesh Eswarawaka 
    Abstract: Microblogs like Twitter emerged as a significant means for instantaneous information sharing on the web and forming the communities of similar interests by recommending the correlated information like tiny URL’s, hash tags, friends or ally’s, etc. to the target users. Existing systems do not capture the dynamic change in the user’s interest over the time while recommending the potential user to the target user. Also, while computing the content similarity of the tweets, the existing systems just instinctively considers the total number of matching words in the two tweets, without considering the semantic similarity or discourse relation between them. In this work, we propose a dynamic and personalised ally recommendation system that computes the user’s interests dynamically and considers the larger matching of semantic orientation of tweets on common topics which are computed based on content similarity of tweets using rhetorical structure theory.
    Keywords: Twitter ally recommendation; rhetorical structure theory; RST; valence shifters; recommendation; HashTag similarity.
    DOI: 10.1504/IJESDF.2023.10052177
     
  • Study on noise control of digital circuit signal transmission under strong magnetic field interference   Order a copy of this article
    by Xiaoxu Zhong 
    Abstract: In order to overcome the problems of low detection rate of strong magnetic field interference, low signal-to-noise ratio and long control time of digital circuit signal transmission noise in traditional control methods, a noise control method of digital circuit signal transmission under strong magnetic field interference is proposed. The mixed signal of digital circuit is extracted, interpolated and power normalised, and the strong magnetic field interference is identified according to the non-stationary degree of signal noise. The input noise signal is segmented in real time from left to right, and the segmented noise subsequence is decomposed by EMD. Combined with the decomposition results, the noise controller structure is designed to realise noise control. Experimental results show that the maximum detection rate of strong magnetic field interference is 98%, the average value of signal-to-noise ratio is 59.4 dB, and the average value of signal transmission noise control time of digital circuit is 73 ms.
    Keywords: strong magnetic field interference; digital circuit; noise control; signal transmission; EMD decomposition.
    DOI: 10.1504/IJESDF.2023.10052178
     
  • A study on methodology on VoIP based communication investigation through network packet analysis   Order a copy of this article
    by Indrajeet Singh, Naveen Chaudhary 
    Abstract: Nowadays mobile communication is changing its definitions from global system for mobile communication (GSM) and code division multiple access (CDMA) communication mechanism to internet-enabled communication mechanisms. In GSM and CDMA technology mobile phone users have to depend upon local service providers. Sophisticated criminals are also aware of the law enforcement agencies’ tactics for GSM/CDMA-based call investigations. VoIP is a voice over internet protocol, an internet-based calling mechanism. VoIP is one of the solutions used by sophisticated criminals for hiding themselves from the ordinary communication mechanism and is an internet-based calling service. In this research, the methodology is discussed and implemented for the identification of VoIP communication using network packet capture and monitoring. This research will cater to the needs of VoIP investigations using network-based packet capturing, analysis and investigation.
    Keywords: voice over internet protocol; VoIP; session initiation protocol; SIP; real-time protocol; RTP; real-time control protocol; RTCP; user datagram protocol.
    DOI: 10.1504/IJESDF.2023.10052265
     
  • Legal awareness and its significance when determining the nature of a person's legal behaviour   Order a copy of this article
    by Ermek Abdrasulov, Akmaral Saktaganova, Indira Saktaganova, Sayash Zhenissov, Zhassulan Toleuov 
    Abstract: Legal awareness is considered a part of consciousness and is an important component of social adaptation. That is why knowledge is especially significant on how legal awareness affects the nature of human behaviour. The purpose of this article is to investigate possible behavioural features of legal behaviour and their relationship with legal awareness, as well as to understand how legal awareness and its qualitative characteristics affect the nature of legal behaviour. Classical methods of information analysis and structuring, methods of classification, logical explanation, finding causal relationships and generalisation were used as research methods. Because of the research, the main provisions of the relationship between the qualities of legal consciousness and the nature of legal behaviour of the individual were formed. Conclusion was made about the influence and the importance of the qualities of legal awareness on the nature of legal behaviour of the individual.
    Keywords: non-conformal legal consciousness; conformal legal consciousness; legal consciousness and religion; social adaptation; defects of legal consciousness.
    DOI: 10.1504/IJESDF.2023.10052307
     
  • Recovery of stolen assets from abroad   Order a copy of this article
    by Rakhmatulla Balashov, Oxana Filipets, Svetlana Baimoldina 
    Abstract: The relevance of the study is due to the exceptional scale of the economic damage caused by corruption crimes, and, as a result, the increased attention of the legislator to countering this group of crimes. According to the World Bank, the cross-border flow of proceeds from crime, corruption and tax evasion is estimated at $1.1 trillion to $6 trillion a year, part of which is stolen from developing countries and countries with so-called 'transitional economies. ' The purpose of the study is to highlight in as much detail as possible the practical issues of returning stolen assets from abroad. The main approaches used in developing the topic are analysis and the comparative legal method. As result, the study expanded and detailed the concept of assets in the context of theft and export abroad, as well as identified a number of gaps and vulnerabilities in asset recovery legislation.
    Keywords: asset recovery; UNCAC; UN convention against corruption; StAR initiative; OECD.
    DOI: 10.1504/IJESDF.2023.10052308
     
  • Cloud Forensics-Enabled Chain of Custody: A Novel and Secure Modular Architecture Using Blockchain Hyperledger Sawtooth   Order a copy of this article
    by Abdullah Ayub Khan, Asif Ali Laghari, Anil Kumar, Zaffar Ahmed Shaikh, Umair Baig, Abdul Ahad Abro 
    Abstract: The exchange of digital information has significantly emerged in the last decade. The increased number of cyber threats over the cloud increases the rate of utilisation of cloud forensics protocols. The lifecycle of cloud computing is getting more affected by the increased number of malicious attacks as more users are sharing, accessing, manipulating, scaling, and reusing data storage. In a cloud forensics environment, it poses a serious issue to provide a confidentiality, integrity, reliability, and trustworthiness platform. This paper overpasses the rift by enabling a novel, secure, and transparent cloud forensics chain-of-custody investigation processes using blockchain. A Hyperledger-Sawtooth provides a secure cloud forensics chain-of-custody investigation architecture is proposed. A private block-based ledger network is setup by a group of people who want to exchange and digitally sign on different parts of a forensics investigation. On the other side, the chain codes implemented to automate transactions of a chain of custody.
    Keywords: blockchain; Hyperledger Sawtooth; smart contracts; NuCypher re-encryption; cloud forensics; chain of custody.
    DOI: 10.1504/IJESDF.2023.10052381
     
  • Human rights information in the context of digitalization   Order a copy of this article
    by Narkes Zhexembayeva, Arailym K. Jangabulova, Guldana A. Kuanalieva, Makhabbat K. Nakisheva, Bahytkul M. Konysbai 
    Abstract: The relevance of the research resides in digitalisation and information technologies introduced into everyday life. For example, a new cluster of so-called digital rights appears during digitalisation, which is not sufficiently developed today. These include the human right to access the internet, the right to protect the user from unwanted information and so on. At the same time, in the legislative systems of a number of states, there are already regulatory legal acts that are aimed at the legal regulation of information. The purpose of this study is a comparative analysis of ways to protect human rights in the context of the introduction of information technologies. Within the framework of the research, along with a number of general scientific methods, special methods are also used. In particular, they include methods of historical analysis, induction and deduction. The information presented in this study can be used by public authorities.
    Keywords: personal data; network security; Kazakhstan; international law; internet; legal regulation.
    DOI: 10.1504/IJESDF.2023.10052382
     
  • Image of the country: problems of information security   Order a copy of this article
    by Assel Abylkhanova, Gulmira Ashirbekova, Galiya Akseit, Aizhan Pernebekova, Bekzhigit Serdali 
    Abstract: Modern post-industrial society is characterised by profound changes in the social structure. Its forms a classless hierarchical system with many social, national and other group differences. This format corresponds to the concept of an open society, but it is characterised by instability, including explained by the presence of a huge number of sources of information about an event or object. One of the consequences of this is social conflicts caused by violations of information security both. Within the framework of this study, there is a consideration of the concept of the image of the country and the phenomenon of information security on the example of the countries of Central Asia, in particular Kazakhstan. The information presented in this article can be used as an introductory for future and current workers in the field of international humanitarian relations, including for a wide range of readers interested in this topic.
    Keywords: post-industrial society; social structure; social conflicts; stereotypes; national security; media sphere.
    DOI: 10.1504/IJESDF.2023.10052419
     
  • Pandemic Outbreak Prediction with An Enhanced Parameter Optimization Algorithm using Machine Learning Models   Order a copy of this article
    by Soni Singh, Dr.K.R.Ramkumar Kumar, Ashima Kukkar 
    Abstract: Several pandemics outbreak has different impact on people in different ways. The modelling of disease is essential to measuring the effect of these pandemics. Several statistical and machine learning (ML) models are developed for making predictions but fail to provide better accuracy. To overcome this, an enhanced prediction model is proposed to increase model accuracy. The parameters of the existing ML models are optimized using the ACO algorithm. Various ML techniques are used to predict the outbreak, such as MLP, SVM, and LR. The performance of the model is tested on COVID-19 and Ebola datasets using accuracy and RMSE score. The result shows that the proposed model yields high accuracy concerning the RMSE score for daily prediction. The MLP-ACO shows better results by comparing with other ML models. The prediction results suggest that the ACO algorithm increases the efficiency of existing ML techniques to predict the outbreak in different countries.
    Keywords: Machine Learning (ML) techniques; Pandemic Outbreak; Parameter optimization; Ant Colony Optimization (ACO); Prediction.
    DOI: 10.1504/IJESDF.2023.10052420
     
  • Defense against Crypto-ransomwares families using Dynamic Binary Instrumentation and DLL injection   Order a copy of this article
    by Digvijaysinh Rathod, Sundaresan Ramachandran, Jeet Rami, Kyounggon Kim, Abhinav Shah 
    Abstract: In recent years, ransomware incidents are increasingly predominant among the nation’s state-sponsored hacker groups. The expertise and ease of deploying ransomware continue to evolve. It is imperative to have comprehensive methods to defend against sophisticated ransomware attacks. This study focused on a two-step approach to classify and prevent file encryption caused by cryptographic ransomware. In this paper, the ransomware families such as Ryuk, Thanos, Cerber, Jigsaw, Teslacrypt, Wannacry, Satana and Lockergoga image loading sequences (ILS) in memory were identified using the Intel PIN tool and developed a method for association mapping to classify crypto-ransomware families. Furthermore, the windows application programming interface (WinAPI) were used for hooking crypto-ransomware samples. It was observed that Kernel32.dll, ADVAPI32.dll, Cryptsp.dll, rsaenh.dll and ws2_32.dll as the most common dynamic linked libraries (DLLs) in the ransomware families. An approach to hook the CreateFileW function in the Kernel32.dll was applied as a proof of concept to prevent file encryption. The results of the present study demonstrated the successful application of DBI to identify and classify new crypto-ransomware variants from similar families and hook the WinAPI function of the Jigsaw, Zemblax and Cerber ransomware.
    Keywords: malware; ransomware; dynamic analysis; binary instrumentation; image loading sequences; ILS; API hooking; DLL injection.
    DOI: 10.1504/IJESDF.2023.10052498
     
  • State immunity as an obstacle in civil proceedings   Order a copy of this article
    by Abylaikhan Aben  
    Abstract: The purpose of the article is to investigate the development of legislation on state immunity, in the presence of alternative dispute resolution options, and the essential need for quick regulation of existing procedural norms regarding state immunity. The article reviews the relevant literature on this topic through analysis and comparison. This paper covers the definition, role, and legal framework of state immunity in civil proceedings. Changes in the development of foreign economic relations have shaken the established theory of absolute immunity of states, and the international community, to establish fair economic relations, has gradually moved to the application of the theory of limited immunity in the form that is in effect today. State immunity still creates barriers in proceedings that not every plaintiff can overcome.
    Keywords: legal basis; civil procedure; court; state; jurisdiction.
    DOI: 10.1504/IJESDF.2023.10052563
     
  • Private detective activity of the law enforcement system of Kazakhstan on the experience of foreign countries   Order a copy of this article
    by Yerbol Alimkulov, Assel Sharipova, Akynkozha Zhanibekov, Gulzhan Mukhamadiyeva, Aizhan Aryn 
    Abstract: The article relevance is due to the need for a new look at the definition of the place of private detective activity in the system of law enforcement agencies. The aims of this article to introduce the ways that will help non-state private detective work do not contradict the state professional law enforcement agencies. The general and special methods, dialectical method of cognition of real reality were used. Historical-legal, structural-system, comparative-legal, logical, sociological, and statistical methods were used as well. This article provides a scientific justification for the consolidation of the Law of the Republic of Kazakhstan 'On private detective activity in the Republic of Kazakhstan'. As a result, scientific approaches to the organisation and legal regulation of private detective work have been developed. The provision of services by a private detective to citizens and organisations should be implemented in strict and obligatory compliance with national legislation and international standards.
    Keywords: private investigation; legal regulation; criminal proceedings; protection of rights; legislation; Kazakhstan.
    DOI: 10.1504/IJESDF.2023.10052564
     
  • Comparative Evaluation of Fully Homomorphic Encryption Algorithms in Cloud Environment   Order a copy of this article
    by Sonam Mittal, Dr.K.R.Ramkumar Kumar 
    Abstract: Cloud computing is an essential component of the service delivery environment in the domain of service computing. It assures a cloud service ecosystem to permit different service providers for participating and provisioning their services for consumers. In the cloud environments, the major component is offering security to the end users, which is ensured with the homomorphic encryption primitives. These approaches focus on minimising the computational burden in terms of clear computation. This paper aims to implement a comparative analysis of privacy preservation in cloud computing using fully homomorphic encryption (FHE) algorithms. A set of algorithms like lattice-based, integer-based, learning with errors (LWE), ring learning with errors (RLWE), and Nth degree truncated polynomial ring units (NTRU) are used for the comparison to make a concluding point regarding those performances. The experimental evaluation demonstrates the efficiency of the diverse frameworks, in terms of both security performance and accuracy, for building a secure analytics cloud-enabled application.
    Keywords: cloud computing; lattice-based fully homomorphic encryption; integer-based fully homomorphic encryption; fully homomorphic encryption; FHE; learning with errors; LWE; ring learning with errors; RLWE.
    DOI: 10.1504/IJESDF.2023.10052607
     
  • Legal mechanism for regulating responsibilities in the information sphere   Order a copy of this article
    by Aigerim Issakhankyzy, Gulnar A. Alibayeva, Ainur A. Sabitova, Serik K. Zhetpisov, Botakoz S. Shansharbayeva 
    Abstract: The relevance is conditioned upon the fact that the information sphere affects the components of the security of the Republic of Kazakhstan, such as political, economic, social, and others. The purpose of the research is to identify all the characteristic features of the legal mechanism of regulation of the information sphere on the territory of the Republic of Kazakhstan, to consider the functioning of this segment, to identify obstacles and legislative. An important component is the study of the problem of the legal mechanism of regulation in the information sphere on the territory of the Republic of Kazakhstan. In the course of the research, several methodological approaches were used, including theoretical-methodological approach, the method of analysing scientific literature, formal-legal method and others. The results obtained in the course of the study will help to eliminate conflicts in the legal norms, as well as to propose methods of reforming this.
    Keywords: legal regulation of the information sphere; information law; labour law; informatisation; digitalisation; methods of reforming.
    DOI: 10.1504/IJESDF.2024.10052611
     
  • The detection of phishing attempts in communications systems   Order a copy of this article
    by KALAICHELVI T, Sulakshana Mane, Dhanalakshmi K. M., Narasimha Prasad S 
    Abstract: Phishing is a very effective form of cybercrime that enables offenders to deceive victims and steal important data. Phishing is now one of the most prevalent types of online fraud behaviour. Phishing attacks may cause their victims to suffer significant losses, including the loss of confidential information, identity theft, businesses, and state secrets. We suggest a threat modelling technique in this research to detect and reduce the cyber-threats that might lead to phishing assaults. To uncover all possible dangers that might result in a phishing attack, the proposed study applies the STRIDE threat design methodology to both use scenarios. The studies’ findings demonstrate the approach’s great effectiveness in identifying phishing URLs, with an accuracy rate of 96.3%, a false-positive rate of 17.2%, a false-negative rate of 23.7%. Various methods related to phishing and the taxonomy of phishing are analysed.
    Keywords: social engineering; cell phone phishing; phishing attack media; phishing assaults; attack stages; phishing method.
    DOI: 10.1504/IJESDF.2024.10052724
     
  • Denim Enumeration and Tabulation Solution for the Garments Manufacturing Environment   Order a copy of this article
    by Muhammad Shakir, Shahid Karim, Shahnawaz Ali, Shahzor Memon, Halar Mustafa, Rabia Shaikh 
    Abstract: As the Denim industry production is growing everyday and the establishing new industries are developing rapidly, the problem that is being faced by the industry is greater time consumption regarding counting the denim product. The main objective of this project is to help Denim Industries use its time effectively. The vision is to modernize the old-school method of finished Denim production. It will help us bridge the gap between the physical and digital world, linking the enumeration technique with desktop applications. An incredibly convenient way of keeping the record of produced Denim. Denim production is the root of the Garment industry's earnings and by digitalizing the enumeration technique, we can make it error-free and speedy. It counts every Denim piece and will also scan the Denim for metal pieces. The desktop application of this project is built using Microsoft Visual Studio.
    Keywords: Denim Counter; Denim Enumeration; Tabulation; Metal-free Denim.
    DOI: 10.1504/IJESDF.2024.10052813
     
  • An effective digital forensic paradigm for cloud computing criminal investigation   Order a copy of this article
    by Ravi Kumar, Kiran Shrimant Kakade, PRISCILLA M, Santhosh K 
    Abstract: Cloud computing has been adopted by a wide variety of businesses and organisations in order to give services to customers in a secure and certified manner, protecting cloud providers from fraudulent actions. To investigate cloud-based cybercrimes, however, cost-effective forensics and successful implementation is essential. The topic has been the subject of several surveys and reviews thus far from researchers. An iCloud investigative tool taxonomy is presented in this study to find the products that meet their technical needs in a searchable catalogue. The authors of this study developed the taxonomy. The research results demonstrated that the recommended solution may effectively help digital inspectors in their mission to look into cloud-based cybercrimes. This research paper aims to analyse the digital forensics issues raised by the cloud computing paradigm and to offer the appropriate solutions and recommendations. Cloud computing and more conventional types of digital forensics are also given in-depth examination.
    Keywords: computer crimes; cloud technology; computer forensics; forensic investigations; forensic software tools; cloud crime; cloud forensics; cloud framework.
    DOI: 10.1504/IJESDF.2024.10052830
     
  • Utilizing Blockchain Technology to Provide Safety for Smart Home Networks   Order a copy of this article
    by Senthilkumar T, Leo John Baptist, MADHINI M, Hemalatha K 
    Abstract: Bitcoin, other cryptocurrencies, and the trading of digital assets were among the first uses for blockchain technology. But blockchain has many other advantages as well. This paper details the application of blockchain technology to the problem of domestic safety. In order to demonstrate how blockchain Technology can be used to secure mobile agents in the IoT, this paper will make use of Ethereum and a smart contract. Malicious mobile agents that attempt to infiltrate internet of things (IoT) systems can be identified through blockchain transactions. The blockchain centre is the central repository for all records, guaranteeing their verifiability and making it impossible to forge them. The outcomes of the evaluations show that the proposed security solutions are superior to the ones currently in use. Our research suggests that the proposed blockchain-enabled solution can enhance smart home security while also allowing for more nuanced user input.
    Keywords: artificial intelligence; AI; blockchain; cloud computing; crypto assets; payments; home security; multi-agent systems; community safety.
    DOI: 10.1504/IJESDF.2024.10052831
     
  • ANALYSIS OF SMART GRID BASED INTRUSION DETECTION SYSTEM THROUGH MACHINE LEARNING METHODS   Order a copy of this article
    by Ravikumar D, Sasikala K, Vijayashanthi R.S., Narasimha Prasad S 
    Abstract: This article aims to maximise network strong security and its enhancement by presenting different preventative strategies since intrusion detection is essential to computer network security challenges. In this study, intrusion detection is addressed as a challenge of extracting outliers that use the network behaviour dataset, and semi-supervised classification technique based on shared closest neighbours are suggested. Provide a thorough explanation of the fundamentals of cyber security assaults, supervised machine learning methods, and intrusion detection systems. Then, we discuss pertinent initiatives related to the use of supervised methods for intrusion detection. Finally, a taxonomy based on these connected works is offered. This article attempts to offer a sophisticated and distinctive intrusion detection model capable of categorising electrical network events and CDs for smart grids into binary-class, trinary-class, and multiple-class categories. As an effective machine learning model for intrusion detection, it employs the grey wolf algorithm (GWA).
    Keywords: databases; support vector machines; smart grids; cyber attacks; intrusion detection systems; IDS.
    DOI: 10.1504/IJESDF.2024.10052832
     
  • Monitor and detect suspicious online transactions   Order a copy of this article
    by Swagata Sarkar, Babitha Lincy R, Sasireka P, Sonam Mittal 
    Abstract: This article provides a thorough examination of phishing attempts, their use, several contemporary visual similarity-based phishing detection systems, and their comparison evaluation. This research article aims to propose an effective design technique for IDS with regard to online applications. We develop a new set of features based on time-frequency analytics that makes use of 2-D models of monetary operations for preventing money laundering systems. As a classification algorithm, random forest is used, and clustering algorithm is used to tune the hyperparameters. Our findings imply that bitcoin exchanges would behave in an excessive reporting manner more than private banks under this law. We specifically take into account the monetary operations as a digital signal and attempt to build a classifier using a collection of frequently mined rules. Our tests on a replicated transaction dataset based on actual banking operations demonstrate the effectiveness of our suggested approach.
    Keywords: random forest technique; time frequency research; graphical study.
    DOI: 10.1504/IJESDF.2024.10052833
     
  • Security of internet of things based on cryptographic algorithm   Order a copy of this article
    by Sonam Mittal, Soni Singh, BALAKUMARAN D, Hemalatha K 
    Abstract: The desire for automated and connected gadgets has managed to become more significant as the globe continues to advance. The internet of things (IoT), a brand-new idea that focuses around the idea of smart gadgets, has been launched in order to address the situation. The results of this analysis are then used to intelligently govern the operational behaviours of these devices. This study fills this need by describing the design, construction, and practical assessment of a fast deployable internet of things architecture that includes embedded data security. We demonstrate that cryptography that depends on the randomness of wireless link is a great option for the IoT technology. We conclude by discussing the challenges and issues that encryption algorithm is now facing and making recommendations for future research in an effort to make key generation a trustworthy and secure defence against the IoT technology.
    Keywords: safety; internet network; cross-layer security; cryptography; cryptographic algorithms; computer hacking.
    DOI: 10.1504/IJESDF.2024.10052834
     
  • Image Encryption Based on 3D Arnold and Elementary Cellular Automata Method   Order a copy of this article
    by Rui Yang, Lijuan Feng, Jiangjiang Li 
    Abstract: The traditional image encryption methods have some problems such as poor security and inefficient encryption, this paper proposes a new image encryption method based on 3D Arnold-oriented elementary cellular automata. The new image encryption method first uses 3D Arnold to scramble pixel positions. Then the elementary cellular automata based on quad-tree decomposition is used to further confuse the scrambled images at the specific level to obtain ciphertext images. The experiment results show that this new method can achieve good encryption effect with fewer iteration times and has strong sensitivity to plaintext and key. It also can effectively resist differential attack.
    Keywords: image encryption; elementary cellular automata; 3D Arnold; quad-tree decomposition.
    DOI: 10.1504/IJESDF.2024.10052835
     
  • Google Chrome Forensics   Order a copy of this article
    by Hitesh Sanghvi, Digvijaysinh Rathod, Salem Yahya Altaleedi, Abdulaziz Saleh AlThani, Mohammed Abd Alrhman Alkhawaldeh, Abdulrazaq Almorjan, Ramya Shah, Tanveer Zia 
    Abstract: Google Chrome is used to explore the internet and navigate websites. Users prefer incognito mode because it claims that it does not keep crucial information in the computer, ensuring privacy and security of browsing data. while, offenders employ incognito mode browsing to perpetrate a crime, digital forensics investigators face new technical obstacles in recovering evidence. We have presented the evidence obtained in Google Chrome while it is open in normal and incognito mode. We performed 78 activities and hard drive and RAM forensics were performed using FTK and autopsy. We unearthed artefacts in the cases of deleted bookmarks and history, Gmail and Yahoo mail, Facebook chat and web WhatsApp chat while Google Chrome is open in normal and incognito mode, credential of Google and Outlook while it is open in incognito mode. Results show that the FTK gives better results than autopsy in terms of evidence extraction using hard-disk forensics.
    Keywords: browser artefacts; digital forensics; internet privacy; incognito mode; normal mode; FTK; autopsy.
    DOI: 10.1504/IJESDF.2024.10052836
     
  • Malicious Program Ontology Rule Set Based on Association Decision and Linear Discriminant   Order a copy of this article
    by Chenghua Tang, Min Hu, Mengmeng Yang, Baohua Qiang 
    Abstract: Aiming at the problems of poor scalability and time-consuming in building inference rule sets manually for malware domain ontology, an automatic generation method of malware ontology rule sets is proposed. We extract the behaviour characteristics of malicious programs by defining a formal extended description method based on the frequency of API calls of malicious programs and combining the frequency of API functions. Based on association rules and decision trees, the behaviour characteristics of malicious programs are mined to form a fine-grained redefined rule set of malicious program categories, and SWRL rule language is used to semantic transform the rule set. In addition, the coarse granularity classification of program behaviour rules is implemented based on Fisher linear discriminant algorithm. The generation efficiency of malware ontology rules generated by us is 10.08 pieces/second, and the inference detection rate of unknown samples reaches 89.92%.
    Keywords: malicious programs; behaviour ontology; SWRL rule set; API functions; behaviour characteristics.
    DOI: 10.1504/IJESDF.2024.10052884
     
  • Data Hiding using Video Steganography   Order a copy of this article
    by Ravichandran C, Ashok Vajravelu, Sankarsan Panda, Sheshang Degadwala 
    Abstract: Video steganography aims to hide the presence of a communication from a hostile third party. One of the techniques recommended in this study is the hash-based least significant bit method for video steganography. The study conducts an in-depth analysis of the numerous enhancements that have been made to the safety of data transmission, as well as the several methods that have been adapted in order to accomplish the same goal. The results of the MATLAB simulation show that the proposed method is superior to other state-of-the-art methods that are currently in use. According to the findings of the comparison, the data-hiding method that has been proposed provides increased safety and reduces distortions for improved video quality. The results of our experiments suggest that our algorithm offers a high level of protection while having just a minimal effect on video quality.
    Keywords: cover video; steganography; LSB technique; watermarking; AES; peak signal-to-noise; intra-prediction mode; integer wavelet transform; temporal correlation.
    DOI: 10.1504/IJESDF.2024.10052934
     
  • SECURITY ENHANCEMENT IN WIRELESS SENSORS USING BLOCKCHAIN TECHNOLOGY   Order a copy of this article
    by Ravichandran C, Ravi Kumar, Senthilkumar T, Ravikishore Veluri 
    Abstract: This study includes blockchain technology that handles each mobile database like one block. First, every block detects its data range. The system then links sensor information for every block to blockchain technology. Every block node stores the sensor data for the entire wireless network after the connection of each block is completed. The module also simultaneously supplies a web server. The internet of things (IoT) topology is used to build up this mobile web server. A blockchain is a concatenated transaction record that is cryptographically protected. To preserve the integrity of wireless sensor networks, they need protection against multiple security infractions. Each block of the suggested technique includes the encrypted risk value of the previous block, the current timestamp, and wireless network sensing data. The proposed system, therefore, collects and analyses sensor data to optimise the setup of the wireless sensing network.
    Keywords: wireless sensor network; blockchain; security; data privacy.
    DOI: 10.1504/IJESDF.2024.10052935
     
  • Formulation of a two-level electronic security and protection system for malls   Order a copy of this article
    by Thirumurugan Thirugnanam, Leena Bojaraj, Lavanya R, Nagalakshmi T.J 
    Abstract: Electronics are everywhere around us these days, and many of them help us maintain security in different locations. However, there are still numerous security issues that banks, residences, and other establishments must deal with. The real-time identification of possibly suspicious actions in shopping malls is the main goal of the comprehensive expert system we present in this article. Our video surveillance technique makes a number of creative suggestions that combine to create a solid application that effectively tracks people’s movements and identifies suspicious activity in a retail setting. The discussion of several present and developing solutions aimed at obtaining a high level of trust in IoT applications follows the discussion of security concerns. Four potential technologies blockchain, edge devices, cloud technologies, and machine learning are examined. An experiment demonstrates that in the same dependable network environment of DCNs, our responsibility security routing system performs better.
    Keywords: electrical gadgets; video monitoring in malls; background removal; RFID tags; barcode reader.
    DOI: 10.1504/IJESDF.2024.10053197
     
  • An original data encryption technique for communication networks
    by A. Rajasekar, KARUNAKARAN A, Sivakumaran C, Sheshang Dipakkumar Degadwala 
    Abstract: A novel secure distribution technique of network communication data is developed based on data encryption algorithm to address the issues of poor transfer effectiveness and high transmission bit error rate in previous transmission methods. In order to design the cipher text protocol, the access to network communication data is controlled by the agentless key publishing protocol. According to the experimental simulation findings in this work, the SM2 method (Supermemo2) can produce a 256-bit key very rapidly. The research’s findings indicate that using link cryptographic algorithms in network communication security can increase security by 25%. The original deep learning chaotic encryption algorithm’s performance flaw is optimised in this research. For wireless communication security, a chaotic neural network approach with dynamic keys is suggested. The experimental findings demonstrate that the technique suggested in this study significantly improves the speed of encryption and decryption as well as the key’s capacity to resist decoding.
    Keywords: neural network; key cryptographic technique; expected release terminal; communication systems; bilinear map-based method; key creation; encryption/decryption algorithms.

  • INTERNET OF THINGS BASED VIRTUAL PRIVATE SOCIAL NETWORKS ON A TEXT MESSAGING STRATEGY ON MOBILE PLATFORMS
    by Alagappan Annamalai, Ramesh Chandra Poonia, Suresh Shanmugasundaram 
    Abstract: A virtual private social network (VPSN) allows a device to communicate securely with a network via the internet. Confidential data may be sent more securely thanks to the encrypted connection; it allows the user to operate remotely and prevents unauthorised parties from listening in. A mobile messaging platform is a text-enabled mailbox on the web. They enable companies and organisations to communicate with clients via text message. Social networking organisations may now use compute resources as a utility instead of creating and managing their computer infrastructures thanks to cloud computing (CC). An example of how a distributed sensor-actor environment might be used in a sociology-technical network is shown in this paper. The results are obtained as regular media access actively is 85.7%, security services in IoT is 85.37%, text attackers is 83.6%, loss of information is 82.8%, and blocking text messages is 91.48%.
    Keywords: internet of things; IoT; cloud computing; virtual private; social; networks; mobile platform.

  • Using DNA to Develop a Lightweight Symmetric Encryption Method to Encrypt the Data of IoT Devices
    by Bassam Al-Shargabi, Rame Jamil Al-Dwairi, Mohammed Abbas Fadhil Al-Husainy 
    Abstract: The security and integrity of the data generated from the internet of things (IoT) devices transmitted via networks must be preserved. Traditional encryption methods are used to encrypt IoT data, but they require more processing power, which IoT devices lack (CPU, memory, storage). In this research, we proposed a DNA-based lightweight symmetric encryption (DLSE) method with simple operations and flexible multi-encryption rounds to be deployed to various IoT devices. The encryption key of the DLSE method is derived from a DNA random sequence to produce a unique key for each round, making it more difficult for attackers to break. The experiments show that the DLSE method has outstanding performance compared to AES and 3DES, with the best encryption time and the best proportion of distortion at the highest level of security. Moreover, the DLSE method proved efficient and can be adapted to meet IoT devices’ computational resources.
    Keywords: lightweight encryption; data encryption; security; multi-round encryption; internet of things; IoT; cyber security; DNA-based lightweight symmetric encryption; DLSE.

  • Detection of Botnet using Deep Learning Algorithm: Application of Machine Learning in Cyber-Security   Order a copy of this article
    by Siva Kumar A, Jency Rubia J, Hima Vijayan, Sivakumaran C 
    Abstract: Machine learning has been made possible as a result of the availability and accessibility of a massive amount of data gathered by internet-connected sensors. The concept of machine learning exhibits and spreads the notion that a computer has the potential to develop itself over the course of time. We investigate a variety of security applications from a variety of angles in which ML models play a key role, and we compare the accuracy outcomes of these models using a variety of conceivable dimensions. To provide an accurate depiction of the qualities associated with security, we have shown the threat model and defence strategies against adversarial attack techniques. The proposed method shows about 88% accuracy for the used data. These attacks are based on the fact that the adversaries are aware of the model.
    Keywords: adversarial attack; security; machine learning; deep learning; LSTM.
    DOI: 10.1504/IJESDF.2024.10053550
     
  • A Retrospective Analysis on Fully Homomorphic Encryption Scheme   Order a copy of this article
    by Sonam Mittal, Dr.K.R.Ramkumar Kumar 
    Abstract: Many researchers of cybersecurity have started a hunt for refining the data encryption models for real-life applications. The security and confidentiality of data over cloud as a third party is a big issue, to the users. To overcome this problem, cloud uses some encryption methods for data security. The FHE, an unconventional technology provides unrivalled capabilities to perform computation on encrypted text to facilitate the secure computation for big-data analysis. The paper presents a review of existing standards of FHE schemes such as lattice-based, integer-based, LWE, RLWE, and NTRU. Various challenges need to be addressed are listed, to model the more competent, effective, and dynamic FHE model. The concepts that underpin these schemes are discussed, and their performance and security concerns. The paper helps to understand the different hurdles that need to be overcome for real-life applications and help to find the direction for their research for better FHE scheme.
    Keywords: fully homomorphic encryption; Gentry; DGHV; learning with errors; LWE; ring learning with errors; RLWE; Nth degree truncated polynomial ring units; NTRU.
    DOI: 10.1504/IJESDF.2024.10053552
     
  • A Comparison Study to Analyze the Data Acquisitions of iOS and Android Smartphones Using Multiple Forensic tools   Order a copy of this article
    by Faleh Alshameri, Katrina Khanta, Stephen Boyce 
    Abstract: Nowadays, most people carry their smartphones with them wherever they go, and it has become one of the primary necessities to not leave your home without. Because of the ever-growing rise in smartphone usage, we store most of our personal information into these handheld devices as they have evolved into an extension of ourselves. Additionally, it is critical to acknowledge how multiple mobile applications are connected to cloud storage. The purpose of this study is to emphasise the significance of data remanence located within mobile devices and how forensic data acquisitions from smartphones prove as high-value evidence in legal cases. We conducted an experimental methodology using various data acquisition tools, such as Magnet AXIOM, oxygen forensic detective, Belkasoft X. and MSAB XRY, to extract data from previously used smartphone devices purchased from an eCommerce website. The study provides a comparative analysis between the data acquisition tools and the following smartphones: Apple iPhone 8, Samsung Galaxy S9+, and Google Pixel 3, to determine which tools are more effective at extracting a specific range of deleted datasets.
    Keywords: smartphone forensics; mobile forensics; internet of things; IoT; forensic data acquisition; digital evidence recovery; android; Apple; iOS.
    DOI: 10.1504/IJESDF.2024.10053589
     
  • Dark web data classification using Deep neural network   Order a copy of this article
    by Sathish Kumar P.J, Jency Rubia J, ANITHA R, Sheshang Degadwala 
    Abstract: The dark web is an overlay network comprised of the darknet, which can only be accessed via specialised software and a predetermined permission scheme. This article investigates the development of dark web intelligence as a means of enhancing cybercrime prevention tactics in several countries. On the basis of machine learning, we develop, analyse, and assess the effectiveness of darknet traffic detection systems (DTDS) in IoT networks. We focussed at the safety features that are available to users, as well as their motivations and the ability to revoke their anonymity. In addition, we perform a depth analysis by automating the process of detecting hostile intent from the darknet. Finally, we compared our proposed system to various already existing DTDS models and showed that our best results are an improvement of between 1.9% and 27% over the models that were previously considered to be state-of-the-art.
    Keywords: darknet; traffic analysis; network management; deep learning neural networks; real-time forensics; darknet traffic detection systems; DTDS.
    DOI: 10.1504/IJESDF.2024.10053710
     
  • Deep Learning-Based Image Forgery Detection System   Order a copy of this article
    by Helina Rajini Suresh, Shanmuganathan M, Senthil Kumar, VIDHYASAGAR BS 
    Abstract: Despite the fact that there are more complex ways of forgery being developed all the time, image forgery detection continues to play an essential part in the field of digital forensics. The problem of counterfeit photographs is today a worldwide problem that is mostly distributed via social networking sites. The ability to identify phoney pictures eliminates the possibility that fraudulent photographs may be used to trick or damage other people. Within the scope of this research, we investigate the deep learning technique to image forgery detection. The proposed model implemented by python language uses input images in batches and a convolutional neural network (CNN) using ResNet50v2 architecture and YOLO weights. We analysed the CASIA v1 and CASIA v2 benchmark datasets. For the purposes of training, we used 80% of the data, and the remaining 20%t was used for testing. 85% accuracy obtained for the dataset.
    Keywords: machine learning; deep learning; image forgery; ResNet50; YOLO; CNN.
    DOI: 10.1504/IJESDF.2024.10053856
     
  • An improved region-based embedding technique for data hiding and image recovery using multiple ROI and RONI   Order a copy of this article
    by Bijay Kumar Paikaray, Debabala Swain, Sujata Chakravarty 
    Abstract: To preserve the sensitive contents of digital images during their transmission, it is essential to hide them with maximum imperceptibility so that intruders will not be able to identify them visually. The image recovery at the receiver end is equally significant because of sensitive images, like medical diagnosis images, satellite images, etc. This paper proposes an improved image hiding technique where the sensitive contents of the image are located in multiple regions. These regions get embedded based on histogram analysis of the region of interest (ROI) pixels then hidden in the region of non-interest (RONI). Further, the reverse operations can be applied to the embedded regions and the hidden data are retrieved from RONI. Using this technique, the embedded regions can be easily extracted, recovered, and fully restored without any loss in data. The proposed work is on multiple ROI with the reliability, integrity, and confidentiality of transmitted images.
    Keywords: multiple ROI; region of non-interest; RONI; medical image; image embedding; hiding; imperceptibility; recovery.
    DOI: 10.1504/IJESDF.2023.10046536
     
  • The criminal confrontation of the cryptocurrency (Bitcoin) and its illegal use   Order a copy of this article
    by Safwan Muhammad Al-Shdaifat 
    Abstract: Cryptocurrency trading is shrouded in confusion in terms of criminal confrontation and proof, and it requires the involvement of criminal law to comply with the principles that govern the law. Accordingly, there is a need for solidarity on the international level to define the legal method in order not to misuse cryptocurrency, and in particular Bitcoin. While legal accuracy in this confrontation is desirable, it depends on the balance between the security imperatives to confront terrorism resulting from the misuse of cryptocurrencies and the requirements to protect human rights. Thus, it comes as a major challenge in criminal law to confront the consequences of dealing in cryptocurrency (Bitcoin) for crimes that may lead to security risks, public order in the state of law, and human rights challenges which are often committed by an exceptional intelligent criminal, and the creation of standards that must be adhered to confront such crimes.
    Keywords: Bitcoin; criminal confrontation; general rules.
    DOI: 10.1504/IJESDF.2023.10051940
     
  • Forensics of a rogue base transceiver station   Order a copy of this article
    by Ahmed Landry Sankara, Ramya Shah, Digvijaysinh Rathod 
    Abstract: Mobile communication systems have become an integral part of daily life, and GSM networks are the most widely used telecommunication technology among mobile users in many nations. In recent years, the incidence of attacks with rogue BTS has risen unexpectedly, primarily in nations where GSM remains the primary telecommunications infrastructure. Using YateBTS as the BTS software, we simulated an attack scenario with IMSI catcher, calls/SMS spoofing and calls/SMS interception. Using forensic software such as EnCase and FTK, we examined Raspberry OS (a Linux-based operating system) and YateBTS. We gathered and recovered important artefacts related to user activity, user authentication activity, system calls messages from Blade RF, call logs, internet traffic log, custom SMS and BTS configurations that would be useful in a court of law. We can reconstruct the truth of the crime using the artefacts recovered. Law enforcement, computer forensic investigators, and the digital forensics research community will benefit greatly from the findings of this study.
    Keywords: GSM; rogue BTS; SDR; YateBTS; BladeRF; BTS forensics; digital forensics; IMSI catcher; SMS spoofing; FTK; EnCase.
    DOI: 10.1504/IJESDF.2023.10047307
     
  • Opensource intelligence and dark web user de-anonymisation   Order a copy of this article
    by Tashi Wangchuk, Digvijaysinh Rathod 
    Abstract: The dark web has emerged as a platform where cybercriminals carry out illegal activities. Attempts to investigate and de-anonymise the suspicious dark web users have not been able to keep up with the pace of the dark web's flourishing coupled with dysfunctional tools and techniques. This study proposes and evaluates a dark web investigation framework using a Python-based tool to harvest data from the dark web to derive intelligence for further investigation using the available opensource intelligence (OSINT) tools. In the experimental implementation of the framework and the tool (Dark2Clear), the tool successfully scraped the hidden service URLs, harvested the e-mail addresses of the dark web users, and suspicious e-mail addresses were used as input to the OSINT tools for gathering intelligence to de-anonymise. It was observed that the framework and tool can be effectively used by the investigators to investigate and de-anonymise suspicious dark web users.
    Keywords: hidden services; opensource intelligence; dark web; investigation framework; de-anonymisation.
    DOI: 10.1504/IJESDF.2023.10047389
     
  • Discover and safe: an automated security management system for educational institutions   Order a copy of this article
    by Irfan Ali Kandhro, Umer Khan, Shahrukh Memon, Mohammad Yasir 
    Abstract: In this paper, we proposed discover and safe (DaS) automatic security system by the help of face recognition. The focus of this automated system is to provide high-level security to manage the entry of people with face detection. This paper proposes haar cascade algorithm with dip libraries to create a camera-based real-time security management system through face detection and recognition. Haar cascade algorithm is an object detection algorithm which is mainly used in identifying face of any image or a real-time video (by webcam or building camera). The DaS framework worked on two phases: 1) to locate whether the VM is an unintended security; 2) to secure mission critical applications. The DaS access system implemented the face encoding scheme to detect the face and eye which works effectively on light and illumination changes. The results show that DaS framework can Armor the VM from obscured security problems and steal hidden doors against the attackers.
    Keywords: face detection; face recognition; security; haar face detection; geometrical approach; pictorial approach.
    DOI: 10.1504/IJESDF.2023.10047966
     
  • Aural-acoustic analysis and gender identification of morphed male and female audios   Order a copy of this article
    by Palak Aneja, Sumit Kumar Choudhary, Surbhi Mathur 
    Abstract: Hiding the identity of the criminal is essential from their perspective to avoid getting caught. Crimes like kidnapping, threat calls, and ransom calls often involve the voice of criminals as a crucial piece of evidence. The person's voice is used in the biometric systems for identification as it is unique. Discriminating gender from the questioned audios helps shorten the list of suspects in any offence. In this paper, male voices were compared with morphed male audio and female voices were compared with morphed female audio. To disguise the identity and to study the reliability of the various speaker identification parameters, the female audios were morphed into male audios; and the male audios were morphed into female audios using the same morphing software. In this experiment, 50 female and 50 male voices samples were converted using morphing software, and auditory and acoustic analysis was done for forensic speaker identification. The aural parameters like speech rate, articulation, delivery of speech, dynamic loudness and acoustic parameters like pitch and formant frequency for five vowels were compared.
    Keywords: audio; male; female; morphing; speaker; identification; disguise.
    DOI: 10.1504/IJESDF.2023.10049794
     
  • Face recognition challenges due to aging: a review   Order a copy of this article
    by Vernika Mehta, Surbhi Mathur 
    Abstract: This review paper aims to identify the challenges faced in the face recognition of a person who is seen after a large age gap, we discuss the factors affecting the facial changes during age progression and how to mitigate those challenges by incorporating various identifying, non-variable parameters basis which even a human can recognise a person after a progressed age. The paper intends to introduce the innate quality of persons known as super recognisers who are able to identify an individual even if they have only seen the childhood picture of the person to be found or identified, or even if only 50% of the face to be identified is visible.
    Keywords: facial changes; face recognition; age progression; innate quality; super recognisers.
    DOI: 10.1504/IJESDF.2023.10050098
     
  • Efficient blockchain addresses classification through cascading ensemble learning approach   Order a copy of this article
    by Rohit Saxena, Deepak Arora, Vishal Nagar 
    Abstract: Bitcoin is a pseudonymous, decentralised cryptocurrency that has become one of the most widely utilised digital assets to date. Because of its uncontrolled nature and Bitcoin users' inherent anonymity, it has seen a significant surge in its use for illegal operations. This necessitates the use of unique methods for categorising the addresses of Bitcoin users. This research classifies and predicts the portion of users' activities that are lawful and unlawful on the Bitcoin blockchain. The dataset contains almost 27 billion samples that are divided into nine user acts, five of which were unlawful. To predict cross-validation (CV) accuracy, ensemble learning algorithms are trained and tested. With cross-validation accuracy of 68.63% and 49.64%, respectively, gradient boosting emerged as the best ensemble learning algorithm for classification and prediction, while bagging emerged as the worst. To get the best classification and prediction, hyperparameter tuning is used to find the optimal parameters, which helped to enhance the cross-validation accuracy of the bagging algorithm to 67.70%, with moderate improvements in the rest of the learning algorithms.
    Keywords: blockchain; Bitcoin; ensemble learning; machine learning; ML; classification; anonymity.
    DOI: 10.1504/IJESDF.2023.10051844
     
  • A survey on electronic natural language applications: current challenges and limitations   Order a copy of this article
    by Muhammad Ameen Chhajro, Asharib Ahmed, Muhammad Ahmed Raza, Abdullah Ayub Khan, Asif Ali Wagan, Asif Ali Laghari 
    Abstract: This paper covers the historical backdrop of natural language processing, including both voice and text. It contains an outline of wide approaches to separating the member's significance through human-language sources of info and executing significant exercises in view of that examination that have been and are presently being utilised. The subject incorporates models from a wide scope of uses, like portable individual colleagues, interactive voice response (IVR) applications, and question addressing. However, in this paper, we also highlight implementation challenges and limitations involved in the deployment on the current NLP-based applications.
    Keywords: natural language processing; NLP; artificial intelligence; AI; interactive voice response; IVR.
    DOI: 10.1504/IJESDF.2023.10052047