Forthcoming and Online First Articles

International Journal of Information and Computer Security

International Journal of Information and Computer Security (IJICS)

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International Journal of Information and Computer Security (30 papers in press)

Regular Issues

  • A Secure Three-Factor Authentication Protocol for Mobile Networks   Order a copy of this article
    by Devender Kumar, Satish Chand, Bijendra Kumar 
    Abstract: User authentication is a necessary mechanism to communicate securely for mobile networks Recently, Xie et al have discussed a three-factor authentication (3FA) scheme using ECC for mobile networks and claimed that it is secure even if the user's two factors are known to the attacker However, in this paper, we cryptanalyze their scheme and find the off-line password guessing and user impersonation attacks in it We also propose a secure 3FA scheme for mobile networks using ECC by removing the weaknesses of their scheme We show the formal security verification of the proposed scheme using the ProVerif tool We discuss its informal security analysis to show that it is resistant to the various known attacks We also present its performance analysis along with the related schemes in terms of computational cost and security features, and show that it offers more security features as compared to the related schemes.
    Keywords: Authentication; user impersonation attack; biometrics; off-line password guessing attack;  mutual authentication.
    DOI: 10.1504/IJICS.2023.10050706
     
  • Trilinear Pairing-Based Cryptosystem Authentication: For Electronic Health Record Security in Healthcare System   Order a copy of this article
    by RAJA SOHAIL AHMED LARIK, Yongli Wang, Irfan Ali Kandhro, Nabila Sehito, Ghulam Ali Mallah, Fayyaz Ali 
    Abstract: Electronic health record (EHR) provides us medical information about the patient and provides the overall history of the individual. EHR works automatically. It gives access to health records and workflow of physician. Authentication, timeliness and accessibility to information between doctors and patients are also maintained by this healthcare cryptosystem. The strong cryptosystem consists of doctors’ and patients’ authentic interaction. Hence, we propose trilinear pairing-based cryptosystem security and authentication using elliptic curve cryptography (ECC) and elliptic curve discrete logarithm problem (ECDLP) techniques. Our proposed model authenticates the patients and doctors by key sharing, transmission and authentication to secure the healthcare system. The analysis outcome shows in the performance, accuracy, time and attacks.
    Keywords: electronic health record; EHR; elliptic curve cryptography; ECC; key sharing; authentication; security.
    DOI: 10.1504/IJICS.2023.10051700
     
  • PBDG: A Malicious Code Detection Method Based on Precise Behavior Dependency Graph   Order a copy of this article
    by Chenghua Tang, Mengmeng Yang, Qingze Gao, Baohua Qiang 
    Abstract: Using behaviour association or dependency to detect malicious code can improve the recognition rate of malicious code. A malicious code detection method based on precise behaviour dependency graph (PBDG) is proposed. We create a stain file index by filtering the stain source blacklist, which not only saves storage space, but also quickly locates instructions. An active variable path verification algorithm is proposed to verify and purify the Source?Sink path. The PBDG and its matching algorithm are constructed to identify the malicious code family of the source program. The experimental results on six data sets show the effectiveness of this method. The introduction of active variable paths reduces the number of paths that need to be traversed by 91.2% at most. In terms of the detection effect of malicious code, especially for web applications, it has a good detection accuracy and a low false positive rate.
    Keywords: malicious code; stain file; path space; behaviour dependency graph; vulnerability detection.
    DOI: 10.1504/IJICS.2023.10052187
     
  • Re-Evaluation of PhishI Game and its utilization in Eliciting Security Requirements   Order a copy of this article
    by Rubia Fatima, Affan Yasin, Lin Liu, Wang Jianmin 
    Abstract: The COVID-19 coronavirus pandemic has sparked considerable alarm amongst the general community and has significantly affected the societal attitudes and perceptions. In the current era, social engineers are applying various strategies to exploit human weakness. Phishing, a social engineering technique, is one of the most widely used and effective ways to undermine human assets. In this research study, firstly, we aim to educate the participants regarding phishing attacks; secondly, the dangers associated with excessive online sharing, and thirdly, how to utilise game scenarios developed by the participants to elicit security requirements. We have employed various research methods, such as, survey, observation, personas development, and scenario-based technique to achieve these objectives. Our re-evaluation results show that the PhishI game effectively educates participants regarding phishing attacks and dangers associated with disclosing excessive online information.
    Keywords: social engineering; phishing attack; awareness; security requirements elicitation; serious game; online information disclosure; human factor.
    DOI: 10.1504/IJICS.2023.10052188
     
  • User Driven General Framework to Cap the Joins in Secure Group Communication   Order a copy of this article
    by Payal Sharma, Purushothama B. R 
    Abstract: In the literature, secure group key management schemes have focused on either rekeying cost or security requirements: forward and backward secrecy. There is little or no work that adds new features to the secure group key management scheme. In the existing key management schemes, any user can join or leave the group any number of times during the group's lifetime. There is a need to restrict the number of times a user joins the group during the group's lifetime. We propose a user-driven general framework wherein a cap is enforced on the number of times a user can join the group. Any existing key management scheme can use this framework. In the proposed scheme, the user is prevented from joining a group, say, more than t>0 times. We analyze the scheme and show that the proposed scheme indeed caps the number of times a user can join the group.
    Keywords: Secure Group Communication; Entry Restriction; Shamir's Secret Sharing; Verifiable Secret Sharing.
    DOI: 10.1504/IJICS.2023.10052719
     
  • A New hybrid chaotic System and its analysis   Order a copy of this article
    by Mandeep Kaur Sandhu, Surender Singh, Manjit Kaur 
    Abstract: In this paper, we introduce and examine a new hybrid hyper-chaotic system named eight-dimensional (8D) hyper-chaotic system. The proposed system is designed by combining the hyper-chaotic systems with some modifications. 8D hyper-chaotic system is sensitive to its initial parameters. Therefore, a grey wolf optimisation algorithm is used to tune its initial parameters. The proposed 8D hyper-chaotic system shows hyper-chaotic behaviour and a unique equilibrium with a large range of parameters and six positive Lyapunov exponents. The analyses of the proposed 8D hyper-chaotic system are achieved using amplitude fluctuations, auto and cross-correlation, pseudo phase space trajectories, and equilibrium points. Besides, Lyapunov exponents, bifurcation diagrams, and butterfly effects are also evaluated by defining the initial conditions and specific parameters. Experimental analyses reveal the presence of chaotic and hyper-chaotic attractors, high accuracy, and stable performance of the proposed 8D hyper-chaotic system. Finally, the proposed 8D hyper-chaotic system is used to design the secret key for showing the application in the field of image encryption. It provides a large keyspace and can resist various security attacks.
    Keywords: hyper-chaotic; chaotic; Lyapunov exponents; bifurcation.
    DOI: 10.1504/IJICS.2023.10053890
     
  • On the Performance of AES Algorithm Variants   Order a copy of this article
    by Mohammed N. Alenezi, Haneen Alabdulrazzaq, Hajed M. Alhatlani, Faisal A. S. AlObaid 
    Abstract: Advanced encryption standard (AES) is frequently used to encrypt data transmission over the internet since it is not prone to practical attacks. Many variants of AES exist with different key sizes and block cipher modes. Choosing an AES variant depends on several factors such as speed, the extent of security required, and the type of the application. As such, it becomes vital to test the performance of these variants to help users choose the most suitable one for their needs. This research presents a performance evaluation of encryption/decryption time and throughput of AES-128, AES-192, AES-256 using modes such as CTR, CBC, CFB, and OFB in Python on various file sizes ranging from 1 MB to 50 MB. The results show a natural pattern where an increase in key size and/or file size prolonged encryption and decryption time. Furthermore, CBC mode was the highest in performance for all key sizes.
    Keywords: security; advanced encryption standard; AES; cryptographic algorithms; block cipher modes; throughput.
    DOI: 10.1504/IJICS.2023.10054850
     
  • A new architecture with a new protocol for m-payment   Order a copy of this article
    by BOUKERS Saâd, Abdelkader Belkhir 
    Abstract: The use of mobile payments by a significant number of consumers in recent years has encouraged without exception all other m-payment actors to invest more in this area. The reasons for this use are diverse and multiple. At the same time, this new situation requires all mobile payment actors to increase their cyber resilience in front of the rapid evolution of the techniques used by cybercriminals to properly secure financial transactions and consumer data in order to further increase the popularity of this payment means in the world. In this context, our contribution consists in offering a new architecture with a new protocol for mobile payment that further strengthens confidence in m-payment. Our solution is universal in its design and implementation and uses the SMS service. It is mainly based on the public key infrastructure (PKI), the session key and national and international digital identities of consumers and merchants.
    Keywords: mobile payment; SMS; digital identity; public key infrastructure; PKI; encryption; digital certificate; certification authority; block cipher; end-to-end encryption.
    DOI: 10.1504/IJICS.2023.10054871
     
  • A Robust Feature Points Based Screen-shooting Resilient Watermarking Scheme   Order a copy of this article
    by Ruixia Yan, Yuan Jia, Lin Gao 
    Abstract: Screen-shooting will lead to information leakage. Anti screen-shooting watermark, which can track the leaking sources and protect the copyrights of images, plays an important role in image information security. Due to the randomness of shooting distance and angle, more robust watermark algorithms are needed to resist the mixed attack generated by screen-shooting. A robust digital watermarking algorithm that is resistant to screen-shooting is proposed in this paper. We use improved Harris-Laplace algorithm to detect the image feature points and embed the watermark into the feature domain. In this paper, all test images are selected on the dataset USC-SIPI and six related common algorithms are used for performance comparison. The experimental results show that within a certain range of shooting distance and angle, this algorithm presented can not only extract the watermark effectively but also ensure the most basic invisibility of watermark. Therefore, the algorithm has good robustness for anti screen-shooting.
    Keywords: blind watermarking; screen-shooting; robustness; invisibility; feature points; QR code; discrete cosine transform; DCT.
    DOI: 10.1504/IJICS.2023.10056328
     
  • Technique for Detecting Hardware-Based Trojans Using a Convolutional Neural Network   Order a copy of this article
    by Ravichandran C, Nagalakshmi T.J., Shyamala Bharathi P, Siva Kumaran 
    Abstract: The hardware Trojan, also known as HT, has emerged as a danger to the integrated circuit (IC) sector and the supply chain, leading to the creation of a plethora of Trojan detection strategies. The detection of HT is very necessary to ensure both the chip’s functionality and its safety. This article discusses a recently discovered risk to integrated circuits (ICs) safety. Using a deep convolutional neural network, the authors of this research offer a novel partial RE-based HT detection algorithm. This method can identify Trojan horses in IC layout photos (DCNN). The suggested DCNN model is made up of many convolutional and pooling layers that are stacked on top of one another. By giving proof of concept implementation of the various approaches to FPGAs, we demonstrate the practicability of the presented strategies by demonstrating how they may be implemented.
    Keywords: hardware Trojan; security; deep neural network; FPGA.
    DOI: 10.1504/IJICS.2023.10056329
     
  • SLAK: Secure Lightweight scheme for Authentication and Key-agreement in Internet of Things   Order a copy of this article
    by Oussama Nahnah, Sarra Cherbal 
    Abstract: Internet of things connect unlimited number of heterogeneous devices in order to facilitate services and hence touching most of daily life fields. However, security concerns are a major obstacle to the development and rapid deployment of this high technology. Thus, securing the authentication process has become very important, as it is necessary to prove the legitimacy of the communication devices. Recently, researchers are proposing several mutual authentication and session key agreement protocols. In this regard, we propose our own improved protocol that relies on login, mutual authentication and the agreement of session key in a safety way to secure communications. For the security evaluation of the proposal, we use the authentication BAN logic and the widely used AVISPA tool. The results prove the achievement of mutual authentication and session key agreement securely. In addition to its safety against some known attacks as eavesdropping and replay attacks. For a performance evaluation, we compare the proposal with recent related works in terms of computational and communication costs. The results show the lightness of our protocol and thus its suitability to heterogeneous IoT devices.
    Keywords: authentication; internet of things; security; elliptic curve cryptography; session key; AVISPA.
    DOI: 10.1504/IJICS.2023.10056330
     
  • Post-Quantum zk-SNARKs from QAPs   Order a copy of this article
    by Ken Naganuma, Masayuki Yoshino, Noboru Kunihiro, Atsuo Inoue, Yukinori Matsuoka, Mineaki Okazaki 
    Abstract: In recent years, the zero-knowledge proof and zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) have drawn significant attention as privacy-enhancing technologies in various domains, especially the cryptocurrency industry and verifiable computations. rnA post-quantum designated verifier type zk-SNARK for Boolean circuits was proposed by Gennaro et al. in ACM CCS '18. However, this scheme does not include arithmetic circuits. Furthermore, it is difficult to use it in various applications. Their paper described the construction of a post-quantum designated verifier zk-SNARK for arithmetic circuits from quadratic arithmetic programs (QAPs) as an open problem. rnRecently, Nitulescu proposed a post-quantum designated verifier zk-SNARK for arithmetic circuits using square arithmetic programs (SAPs), which are the special cases of QAPs. rnIn this paper, we give other answers to this problem and propose rntwo post-quantum designated verifier zk-SNARK schemes for arithmetic circuits using QAPs. Our first proposal is based on the data structure used in Pinocchio, a previous study, and can be easily implemented using the existing Pinocchio-based systems. Furthermore, this scheme does not require strong security assumptions. rnIn our second proposal, which also employs QAPs, the zero-knowledge proof comprises three learning with errors (LWE) ciphertexts, and the size of the proof is smaller compared with that of the first proposal. Our second proposal is also more efficient than the first one or all other known post-quantum zk-SNARKs. rnWe implemented our proposed schemes and other known schemes using the libsnark library. Our experimental results show that the second scheme is faster than the previous post-quantum zk-SNARK schemes. rnThe second scheme can generate a zero-knowledge proof for an arithmetic circuit that comprises $2^{16}$ gates in a processing time of only 50 s, which is approximately three times faster than that of the post-quantum zk-SNARKs by Gennaro et al. or two times faster than the one by Nitulescu.
    Keywords: Zero-knowledge proof; zk-SNARKs; LWE encryption; Blockchain technology; Post-quantum cryptography.

  • Multi-level Image Security using Modified Rubik’s Cube Algorithm   Order a copy of this article
    by Rupesh Sinha, Sitanshu Sekhar Sahu 
    Abstract: With the rapid growth in usage of multimedia images and digital data exchange, it is very important to safeguard the images from unauthorised access. In this context, we proposed a multi-level chaotic encryption scheme using modified Rubik’s cube algorithm. First, the original image is jumbled using two secret keys. These keys are generated using chaotic functions with different parameters. Then rows and columns of the jumbled image are again mixed with XOR operator. Performance of the proposed work is evaluated with correlation coefficient (CC), number of pixel change rate (NPCR) and unified average changing intensity (UACI). From the experimental analysis and parameters evaluation it is observed that the proposed scheme can resist exhaustive attack, statistical attack as well as differential attack.
    Keywords: image security; multi-level chaotic encryption; Rubik’s algorithm; XOR operator; correlation coefficient.
    DOI: 10.1504/IJICS.2023.10057698
     
  • Robust watermarking of Medical Images using SVM and hybrid DWT-SVD   Order a copy of this article
    by Kumari Suniti Singh, Harsh Vikram Singh 
    Abstract: In the present scenario, the security of medical images is an important aspect in the field of image processing. Support vector machines (SVMs) are a supervised machine learning technique used in image classification. The roots of SVM are from statistical learning theory. It has gained excellent significance because of its robust, accurate, and very effective algorithm, even though it was applied to a small set of training samples. SVM can classify data into binary classification or multiple classifications according to the application’s needs. Discrete wavelet transform (DWT) and singular value decomposition (SVD) transform techniques are utilised to enhance the image’s security. In this paper, the image is first classified using SVM into ROI and RONI, and thereafter, to enhance the images diagnostic capabilities, the DWT-SVD-based hybrid watermarking technique is utilised to embed the watermark in the RONI region. Overall, our work makes a significant contribution to the field of medical image security by presenting a novel and effective solution. The results are evaluated using both perceptual and imperceptibility testing using PSNR and SSIM parameters. Different attacks were introduced to the watermarked image, which shows the efficacy and robustness of the proposed algorithm.
    Keywords: support vector machine; SVM; discrete wavelet transform; DWT; singular value decomposition; SVD; watermark embedding; image watermarking.
    DOI: 10.1504/IJICS.2023.10057699
     
  • An Image Encryption Using Hybrid Grey Wolf Optimization and Chaotic Map   Order a copy of this article
    by Ali Akram Abdul-Kareem, Waleed Ameen Mahmoud Al-Jawher 
    Abstract: Image encryption is a critical and attractive issue in digital image processing that has gained approval and interest of many researchers in the world. A proposed hybrid encryption method was implemented by using the combination of the Nahrain chaotic map with a well-known optimised algorithm namely the grey wolf optimisation (GWO). It was noted from analysing the results of the experiments conducted on the new hybrid algorithm, that it gave strong resistance against expected statistical invasion as well as brute force. Several statistical analyses were carried out and showed that the average entropy of the encrypted images is near to its ideal information entropy.
    Keywords: cryptography; optimisation algorithm; grey wolf optimisation; GWO; chaotic system; chaos; security applications; secure communication.
    DOI: 10.1504/IJICS.2023.10057701
     
  • Efficient Multi-party Quantum Key Agreement Protocol Based on New Bell State Encoding Mode   Order a copy of this article
    by Zexi Li, Kefan Cheng, Yan Sun, Hongfeng Zhu 
    Abstract: Although there are many quantum key agreement protocols currently in existence, they cannot be merged in terms of resource utilisation, efficiency, security, and other aspects, and there are also significant differences in the nature of two and more parties. Therefore, it is necessary to design a quantum key agreement protocol that can balance efficiency and security and is suitable for multiple participants. In view of this, this paper proposes a multi-party quantum key agreement protocol based on a new coding mode of bell state: temporary session keys are negotiated between adjacent participants, and then shared keys for all participants are negotiated through the exchange, conversion, and computation of quantum resources. During the implementation of the protocol, not only can the identity of the participants be authenticated, but also the quantum resources used are single, and the quantum operations performed are simple. Moreover, efficiency is fixed and does not decrease due to the increase of participants or quantum resources. In addition, the protocol also allows participants to dynamically join and leave. In terms of security, the protocol can resist most common quantum attacks. Under the existing quantum technology, this protocol is completely feasible.
    Keywords: bell state encoding; multi-party; quantum key agreement; QKA; authentication.
    DOI: 10.1504/IJICS.2023.10057985
     
  • Secure Digital Academic Certificate Verification System using Blockchain   Order a copy of this article
    by Sunil Patel, Saravanan Chandran, Purushottam Kumar 
    Abstract: At present, there is a need for an authentic and fast approach to certificate verification. Which verifies and authenticates the certificates to reduce the extent of duplicity and time. An academic certificate is significant for students, the government, universities, and employers. Academic credentials play a vital role in the career of students. A few people manipulate academic documents for their benefit. There are cases identified where people produced fake academic certificates for jobs or higher education admission. Various research works are developing a secure model to verify genuine academic credentials. This research article proposed a new security model which contains several security algorithms such as timestamps, hash function, digital signature, steganography, and blockchain. The proposed model issues secure digital academic certificates. It enhanced security measures and automated educational certificate verification using blockchain technology. The advantages of the proposed model are automated, cost-effective, secured, traceable, accurate, and time-saving.
    Keywords: digital academic certificate; DAC; hash function; blockchain technology; digital signature; steganography.
    DOI: 10.1504/IJICS.2023.10058109
     
  • WTSEMal: A Malware Classification Scheme Based on Wavelet and SE-Resnet   Order a copy of this article
    by Dongwen Zhang, Shaohua Zhang, Guanghua Zhang, Naiwen Yu 
    Abstract: Aiming at the problem that traditional malware feature extraction data is huge and features are diverse, which requires lots of reverse engineering expertise and the detection effect is poor. In this study, we propose a visual malware classification scheme based on Wavelet and SE-Resnet network named WTSEMal. Firstly, convert the binary file of the malware sample into an image format. Then, after the image is pre-processed by normalisation, mean filtering and data augmentation, the image is decomposed and reorganised by wavelet transform (WT). Finally, the reconstructed image is input into SE-Resnet network for family classification. The experimental results show that the accuracy of the proposed WTSEMal classification scheme in malimg and Big15 is 99.22% and 97.49%, respectively, which are better than the existing machine learning malware classification methods. Compared with traditional classification methods, it has a good detection effect in detecting confusion or variant samples, and has strong generalisation ability.
    Keywords: malware detection; wavelet transform; WT; malware visualisation; deep learning.
    DOI: 10.1504/IJICS.2023.10058896
     
  • Feature-driven intrusion detection method based on improved CNN and LSTM   Order a copy of this article
    by Jing Zhang, Yufei Zhao, Jiawei Zhang, Lin Guo, Xiaoqin Zhang 
    Abstract: To make up the lack of detection capabilities of traditional machine learning methods. A network intrusion detection method based on improved convolutional neural network (CNN) and improved long and short-term memory network (HMLSTM) is proposed. The proposed method is mainly divided into four steps, namely data pre-processing, feature extraction, model training and detecting. First, we use the normalisation technology to pre-process the data; and then we use the lion swarm optimisation (LSO) algorithm to optimise the hyperparameters of the CNN to form the optimal CNN (OCNN) structure, and combine HMLSTM model to extract the spatial and temporal features. Finally, we use the spatial-temporal feature vectors to train and detect the upper classifier of OCNN-HMLSTM. This paper selects three commonly used datasets to do lots of experiments. The results show that the proposed method significantly improves the accuracy of network intrusion detection, and other metrics.
    Keywords: feature-driven; intrusion detection; convolutional neural network; CNN; long-short-term memory; LSTM.
    DOI: 10.1504/IJICS.2023.10059327
     
  • A Taxonomy of DDoS Attacks and its Impact on Docker Architecture   Order a copy of this article
    by Sushant Chamoli, Varsha Mittal 
    Abstract: Cloud infrastructure has become a favourite target for attackers as more and more organisations are switching to it owing to features like availability, scalability, and cost savings. Virtualisation has been the core of cloud computing and Docker containers are picking up ubiquity as a virtualisation tool, owing to their lighter weight and quicker start-up times. However, because the containers share the underlying host kernel, any container-level attack can have serious consequences for the host system. This study analyses and categorises the DDoS attack
    Keywords: distributed-denial-of-service; DDoS; distributed denial of service; Docker; cloud; security; taxonomy.
    DOI: 10.1504/IJICS.2024.10061783
     
  • Machine Learning and Deep Learning Techniques for Detecting and Mitigating Cyber Threats in IoT-Enabled Smart Grids: A Comprehensive Review   Order a copy of this article
    by Aschalew Tirulo, Siddharth Chauhan, Kamlesh Dutta 
    Abstract: The confluence of the internet of things (IoT) with smart grids has ushered in a paradigm shift in energy management, promising unparalleled efficiency, economic robustness and unwavering reliability. However, this integrative evolution has concurrently amplified the grid’s susceptibility to cyber intrusions, casting shadows on its foundational security and structural integrity. Machine learning (ML) and deep learning (DL) emerge as beacons in this landscape, offering robust methodologies to navigate the intricate cybersecurity labyrinth of IoT-infused smart grids. While ML excels at sifting through voluminous data to identify and classify looming threats, DL delves deeper, crafting sophisticated models equipped to counteract avant-garde cyber offensives. Both of these techniques are united in their objective of leveraging intricate data patterns to provide real-time, actionable security intelligence. Yet, despite the revolutionary potential of ML and DL, the battle against the ceaselessly morphing cyber threat landscape is relentless. The pursuit of an impervious smart grid continues to be a collective odyssey. In this review, we embark on a scholarly exploration of ML and DL’s indispensable contributions to enhancing cybersecurity in IoT-centric smart grids. We meticulously dissect predominant cyber threats, critically assess extant security paradigms, and spotlight research frontiers yearning for deeper inquiry and innovation.
    Keywords: smart grid; cyber threats; cybersecurity; internet of things; IoT; deep learning; machine learning.
    DOI: 10.1504/IJICS.2024.10061784
     
  • An Intelligent Approach to Classify and Detection of Image forgery attack (Scaling and Cropping) using Transfer Learning   Order a copy of this article
    by Ravi Sheth, Chandresh Parekha 
    Abstract: Image forgery detection techniques refer to the process of detecting manipulated or altered images, which can be used for various purposes, including malicious intent or misinformation. Image forgery detection is a crucial task in digital image forensics, where researchers have developed various techniques to detect image forgery. These techniques can be broadly categorised into: active, passive, machine learning-based and hybrid. Active approaches involve embedding digital watermarks or signatures into the image during the creation process, which can later be used to detect any tampering. On the other hand, passive approaches rely on analysing the statistical properties of the image to detect any inconsistencies or irregularities that may indicate forgery. In this paper for the detection of scaling and cropping attack a deep learning method has been proposed using ResNet. The proposed method (Res-Net-Adam-Adam) is able to achieve highest amount of accuracy of 99.14% (0.9914) while detecting fake and real images.
    Keywords: image forgery; scaling; cropping; deep learning; transform learning; ResNet.
    DOI: 10.1504/IJICS.2024.10062129
     
  • A Novel Blockchain Consensus Protocol with Quantum Private Comparison for Internet of Vehicles   Order a copy of this article
    by Kefan Cheng, Lu Zhang, Yan Sun, Hongfeng Zhu 
    Abstract: Consensus protocols are a key feature in decentralised systems/networks which aiming to obtain and agree on a shared state among multiple unreliable nodes with diverse applications. Therefore, that integrated design with new technologies will become a difficult and hot research topic, especially in combining new fields such as quantum information and blockchain. Spontaneously, we propose a new consensus protocol in combination with quantum private comparison (QPC) in internet of vehicles (IoV) using practical Byzantine fault tolerance (PBFT) to achieve security and efficiency at higher levels. Through multi-node collaborative computing, different vehicles can quickly reach a consensus. More importantly, we have added quantum technology in the identity authentication and consensus phase, which can make our integrated network more robust and prevent malicious attacks. In other words, our protocol adopts QPC to make it impossible for any malicious node to maliciously disturb the order between nodes in the consensus phase, thus improving security. Finally, compared with the recent related literature, our consensus protocol has strong practicability and universality and can be well applied in the IoV environment.
    Keywords: quantum cryptography; quantum private comparison; internet of vehicles; IoV; blockchain.
    DOI: 10.1504/IJICS.2024.10062130
     
  • Generating key-dependent involutory MDS matrices through permutations, direct exponentiation, and scalar multiplication   Order a copy of this article
    by Tran Thi Luong, Hoang Dinh Linh 
    Abstract: Block ciphers are a crucial type of cryptographic algorithm being used to ensure information security for many applications today. However, there are numerous potential active attacks on block ciphers, so the research and design of dynamic block ciphers to advance the security of block ciphers is a matter of concern today. Maximum distance separable (MDS) matrices are a crucial component of many block ciphers. Involutory MDS matrices are primarily selected because using an involutory matrix allows for both encryption and decryption operations to be performed using the identical circuitry, resulting in an equal implementation cost for both processes. In this article, we propose algorithms to generate 4 x 4 and 8 x 8 Hadamard involutory MDS matrices based on column and row permutations. Next, we propose an algorithm to create key-dependent involutory MDS matrices based on column and row permutation, scalar multiplication, and direct exponentiation. Then, we experimentally strengthen the dynamic AES block cipher based on the proposed algorithm, conduct security analysis, and evaluate the NIST statistical criteria for AES and the dynamic AES algorithm. The outcomes of our research could potentially enhance the robustness of the AES block cipher against numerous contemporary powerful attacks.
    Keywords: MDS matrix; Hadamard involutory MDS; AES; dynamic AES.
    DOI: 10.1504/IJICS.2024.10062529
     

Special Issue on: Security and Privacy for Emerging Technology

  • The Relationship between Digital Information Security of the Supply Chain and Enterprise Development   Order a copy of this article
    by Zhezhou Li, Xiangrong Kong, Xiaozhen Jiang 
    Abstract: This study aims to enhance the core competitiveness of enterprises in the competitive environment and realise the rapid and sound development of enterprise security. The relationship between the digital transformation of the supply chain and the core competitiveness of enterprises is discussed from the perspective of constructing the information security (IS) of the internet of things (IoT). Firstly, the ciphertext-policy attribute-based encryption (CP-ABE) model of the information centre is established to study the technical problems of information encryption of IoT enterprises. Secondly, the correlation analysis method is used to determine the impact of supply chain transformation on the future development of enterprises through the correlation between the digital transformation of the supply chain and enterprise competitiveness. Finally, targeted solutions are proposed for the digital transformation of the supply chain and the IS of IoT of enterprises.
    Keywords: information security of the internet of things; supply chain digital transformation; algorithm response time; core competitiveness of enterprises; correlation analysis.
    DOI: 10.1504/IJICS.2023.10057702
     
  • Encryption by block based on rekeying and inter-intra pixel permutation   Order a copy of this article
    by Rachid RIMANI, Adda Ali Pacha, Naima HADJ SAID 
    Abstract: The growing use of ICT exposes exchanges to certain risks, which require the existence of adequate security measures of information. The data encryption is often an effective way to meet these requirements of security and confidentiality. This paper present a novel cryptosystem by block depended on the secret key and subkeys and respect the fundamental principles of modern cryptography for encrypting images, since images have some intrinsic features such as large data capacity, strong correlation between adjacent pixels and high redundancy of information. The proposed cryptosystem is based on rekeying to apply permutation inter-intra pixel of each block according to the secret key and subkeys using a random, nonlinear, dynamic and secret scrambled technique there be called RNDSS. Experimental tests demonstrate the high security of the proposed cryptosystem with RNDSS technique and show the high sensitive dependence to any subtle change in the secret key, which guarantees the security against brute force attacks.
    Keywords: cryptosystem by block; permutation inter-intra pixel; rekeying; RNDSS technique; secret key.
    DOI: 10.1504/IJICS.2024.10061312
     
  • Enterprise Intelligent Financial Sharing Mechanism in the Security Environment of the Internet of Things   Order a copy of this article
    by Yongling Zhang, Xuandong Zhang, Jinlong Song 
    Abstract: This study aims to enhance the functional development of enterprise intelligent financial sharing and ensure the security of financial information transmission within organisations. It begins by comprehensively understanding the current state of the internet of things (IoT) security environment and the establishment of enterprise intelligent financial sharing mechanisms. Subsequently, this study analyses and discusses the continuous identity authentication and security threat assessment control model in the context of IoT security under decentralised computing. Finally, the grey clustering trigonometric function evaluation model is employed to establish a functional evaluation mechanism for enterprise intelligent financial sharing, thereby improving the functionality of financial sharing. The findings indicate that IoT data exhibits the highest levels of security and reliability. By continuously controlling the attack rate below 0.2, the number of malicious nodes is significantly reduced, leading to a basic guarantee of IoT information security.
    Keywords: sharing of intelligent enterprise finance; internet of things security; continuous identity authentication; indicator integration; grey clustering.
    DOI: 10.1504/IJICS.2024.10061313
     
  • Library Data Protection and Threat Detection System Based on Network Security   Order a copy of this article
    by Jianxin Xiong, Xianping Wang 
    Abstract: Traditional libraries may have security risks such as data breach, network attack and virus infection, which requires a library data protection and threat detection system based on network security to effectively manage and protect. Based on the premise of network security, this article focused on analysing library data protection and threat detection, constructing a library data protection and threat detection system using encryption algorithms, and testing its performance. According to the experimental results, it can be concluded that the average response time of unknown threats in the library data protection and threat detection system based on network security ranged from 0.4s to 0.8s under different test times. It can be seen that the system not only performs well, but also has very good user satisfaction. This article aimed to ensure the security of users’ use of library resources and services through effective threat detection and data protection measures.
    Keywords: library data protection; threat detection; network security; encryption algorithm; security vulnerability scanning; data breach.
    DOI: 10.1504/IJICS.2024.10061565
     
  • Analysis of Competitive Differences in the Bilateral Platforms of the Digital Economy Using Artificial Intelligence and Network Data Security   Order a copy of this article
    by Jingfeng Jiang, Yongyi Wu 
    Abstract: This work aims to conduct a more precise and secure analysis of the competitive differences in bilateral platforms of the digital economy based on AI and network data security. The application of Artificial Intelligence (AI) technology on bilateral platforms can significantly enhance the level of intelligence and personalization in services. However, it also drives continuous advancements in data security technology. This work explores the characteristics and advantages of different platforms, providing decision support and strategic guidance to relevant institutions and businesses. Based on this, this work first establishes a distributed training scheme under fog computing to counter data poisoning and safeguard privacy. This scheme is utilized for data collection, storage, and processing while incorporating stringent measures for data privacy protection, such as data encryption, identity authentication, and access control.
    Keywords: artificial intelligence; network data security; digital economy; bilateral platforms; analysis of competitiveness differences.
    DOI: 10.1504/IJICS.2024.10061566
     
  • The Optimization of Enterprise Internet of Things Security Management System under Digital Economy   Order a copy of this article
    by Jianhua Liu, Huijie Ma 
    Abstract: In the context of the digital economy, this study integrates the Internet of Things (IoT), blockchain, ant colony optimization (ACO), neural network, and other modern digital information technologies. An enterprise IoT Security Management System (SMS) is built to address the security risks of enterprise IoT information and data. The improved backpropagation (BP) algorithm optimizes data transactions and network security templates in enterprise IoT SMS. At the same time, this study also introduces the ACO to improve the performance of the BP neural network. Firstly, the methods of enterprise IoT security management under the growth of the digital economy and the technical path of digital technology for enterprise security management are explained. Secondly, a BP algorithm based on an ant colony algorithm and genetic algorithm optimization is established to improve the speed and security of data transactions and network security module processing information data in the enterprise IoT SMS.
    Keywords: Digital economy; Internet of Things; Blockchain; Enterprise security management; System optimization; Ant colony optimization.
    DOI: 10.1504/IJICS.2024.10061567