Forthcoming and Online First Articles

International Journal of Internet Technology and Secured Transactions

International Journal of Internet Technology and Secured Transactions (IJITST)

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International Journal of Internet Technology and Secured Transactions (8 papers in press)

Regular Issues

  • Implementation of Bixby oriented electric vehicle charging station searching service   Order a copy of this article
    by Jihoon Lee, Eugene Rhee 
    Abstract: As the electric vehicle market has significantly grown, the needs to install the charging station infrastructure for electric vehicles (EVs) have also been increased. Therefore, it is required for the efficient searching scheme for the appropriate charging station to enhance user experience. However, existing EV charging station searching schemes have low user convenience because they just provided the location information of the charging stations. Also, they did not provide user-friendly location information as well as voice recognition functionality. To overcome such limitations, this paper shows the voice recognition based EV charging station search scheme using Bixby platform to enhance user experience.
    Keywords: Bixby platform; EV charging station; voice recognition; searching scheme.
    DOI: 10.1504/IJITST.2022.10049722
     
  • Network intrusion detection using meta-heuristic feature selection and cost-sensitive learning   Order a copy of this article
    by Ritinder Kaur, Neha Gupta 
    Abstract: In contemporary society, networked computers are playing a pivotal role in dissemination of knowledge and critical data in information systems and ensuring its security has become a challenging task for the network administrators and researchers. Machine learning techniques are extensively used in intrusion detection systems to mine out the extensive network data and extrapolate attack patterns. This paper proposes an intrusion detection framework with a combination of diverse attribute selection algorithms and machine learning algorithms to provide effective intrusion detection. Firstly, the model extracts the most relevant attributes using a hybrid meta-heuristic feature selection algorithm and then applies supervised machine learning algorithms to detect the several attack classes with improved detection accuracy, execution time and error rate. This study used NSL-KDD dataset on the proposed CS-CFSMHA framework with AdaBoost ensemble technique. Cost-sensitive classification was applied which improved the minority class accuracy and the overall accuracy to 81.1%.
    Keywords: machine learning; intrusion detection; feature selection; NSL-KDD; swarm techniques; meta-heuristic search: cost-sensitive learning.
    DOI: 10.1504/IJITST.2022.10050202
     
  • Credit card fraud detection using predictive features and machine learning algorithms   Order a copy of this article
    by Naoufal Rtayli, Nourddine Enneya 
    Abstract: CCF can destabilise economies, reduce confidence between customers and banks, and severely affect other people and businesses. The primary objective of banks and businesses is to identify fraudulent transactions with a high level of accuracy. Also, reduce false alerts and the costs of manual investigation activities. When identifying CCF in large datasets, feature selection is very important to improve accuracy performance and rapid detection of fraud. One of the most widely used methods of feature selection is the random forest classifier (RFC), which is well suited for large datasets. The RFC works well; it tends to identify more predictive features, which can significantly improve the classification performance for a CCF detection model. In this paper, we suggest a CCF detection method based on feature selection using random forest classifier and machine learning algorithms such as support vector machines (SVM), isolation forest (IF) to detect fraudulent transactions. The proposed model is applied to a large real-world dataset to study the accuracy of its fraud detection performance. A comparison is made between the proposed model and other machine learning methods.
    Keywords: machine learning; credit card fraud detection; feature selection; massive data.
    DOI: 10.1504/IJITST.2022.10051923
     
  • Employment contract and wage payment using blockchain and smart contract   Order a copy of this article
    by Eugene Rhee 
    Abstract: Employment contracts recorded on blockchain have the strength to make it impossible to falsify or modify the agreements between employers and employees. The fact is that the work input through the application remains on the blockchain, and the manager shares it, which is expected to significantly improve the disadvantaged position of part-time workers. As a way to recognise and solve recent problems with employment contracts and wage problems, this paper proposes to store employment contracts in blocks using blockchain technology, enable accurate wage payments using smart contracts, and also store wage information in blocks. In addition, it can be proved by using the contents stored in the block when problems occur later.
    Keywords: blockchain; employment contract; Ethreum; smart contract.
    DOI: 10.1504/IJITST.2021.10041613
     
  • An enhanced security framework for IoT environment using Jaya optimisation-based genetic algorithm   Order a copy of this article
    by S. Velliangiri, Iwin Thanakumar Joseph, Shanthini Pandiaraj, P. Leela Jancy, Ch. Madhubabu 
    Abstract: The internet of things (IoT) employs a cloud network, and the data stored in the cloud servers are highly vulnerable to various attacks. As per the current analysis report, around 23% of IoT devices are prone to attack. The data stored in the cloud storage are highly vulnerable to attacks leading to a pullback factor of 15% in economic growth. Considering the above security of the IoT devices, this paper proposes a framework integrating the Jaya algorithm and genetic algorithm to achieve an optimal detection of intrusion in the IoT network. The JA is a parameter less algorithm that does not require any precise control parameters. In contrast, the GA is a meta-heuristic approach that produces reasonable quality solutions for complex functions. The extensive analysis of the proposed algorithm yield better performance in vital parameters like accuracy, recall and F-score.
    Keywords: internet of things; IoT; cloud storage; data access; Jaya algorithm; JA; genetic algorithm; GA; security; privacy.
    DOI: 10.1504/IJITST.2022.10047960
     
  • A comprehensive blockchain technology survey: architecture, applications and challenges   Order a copy of this article
    by Gajala Praveen, Piyush Kumar Singh, Prabhat Ranjan 
    Abstract: Blockchain technology has evolved to solve the complexity and privacy issues associated with online digital content distribution in the last decade. Several studies have centred on different implementations of blockchain technology, and there is no comprehensive survey of the technology from both a technical and an application viewpoint. To close this gap, we conducted a detailed blockchain technology survey. This paper gives an in-depth look at blockchain technology. It discusses the blockchain fundamentals, taxonomy, characteristics, architecture of blockchain, and accessible consensus mechanisms used in the various blockchain systems. This paper also gives blockchain applications in multiple domains, including finance, medical, banking, etc. In addition, this paper presents an overview of the various problems that currently exist in blockchain technology and future research directions.
    Keywords: Bitcoin; consensus algorithms; smart contract; blockchain architecture; blockchain applications; blockchain challenges.
    DOI: 10.1504/IJITST.2022.10048331
     
  • A novel verification framework to analyse security attacks in a fingerprint authentication system   Order a copy of this article
    by D. Harikrishnan, N. Sunilkumar, Shelbi Joseph, Kishor Krishnan Nair 
    Abstract: The security vulnerabilities and flaws in the existing biometric fingerprint authentication system (FAS) are effectively overcome using the one time finger code (OTFC). Based on this OTFC technique, a new verification model is proposed in this work which is capable of evaluating and analysing the susceptibility of system to common security attacks. For verification and validation compliance, an integrated security framework with novel security protocol along with generation of a unique encryption key named terminal key is conceptualised and implemented. The exposure of the system to various security attacks are experimentally computed by measuring avalanche effect, which fetches an average value of 63.52%. Also, the severity of attack is verified by calculating base score obtained as 3, which is less in comparison with conventional systems. Hence it concludes that proposed FAS with new verification framework yields better results on exposure to common security threats than the conventional one.
    Keywords: one time finger code; OTFC; fingerprint authentication system; FAS; attacks; security; avalanche effect; base score; biometric; fingerprint; terminal key; algorithm; man in the middle; MITM; replay attack; relay attack; mutual authentication.
    DOI: 10.1504/IJITST.2022.10049155
     
  • Implementing security in IoT systems via blockchain   Order a copy of this article
    by Anurag Parcha, Sanjana Mishra, Aditya Bist, Reema Agarwal, Sagar Gupta, Saahil Sharma, R. Sathyaraj 
    Abstract: Today, IoT systems have become prominent, especially in the fields of healthcare, agriculture, and manufacturing. IoT systems encompass numerous devices that become targets for attacks and exploitation, thereby making these systems prone to security vulnerabilities. While IoT has become a widespread technology by virtue of its scalability, dependability, and ease of access, its shortcomings should also be addressed. Currently, client-server model of networking is employed in IoT devices which use a single gateway for transferring data and connecting through a cloud server. This model demands a high cost for cloud maintenance and network equipment. Furthermore, a single gateway is not secure as one failed node can compromise the entire network. To improve security, we propose the inclusion of blockchain technology; a distributed ledger where data is stored across several nodes, thereby eliminating single point failure. This project proposes the benefits of blockchain technology in conjunction with security of IoT systems.
    Keywords: blockchain; internet of things; IoT; security; networks; blockchain architecture.
    DOI: 10.1504/IJITST.2022.10049251