Suspicious transaction detection in banking cyber–physical systems. (January 2022)

• Record Type: Journal Article
• Authors: Shabbir, Aysha; Shabir, Maryam; Javed, Abdul Rehman; Chakraborty, Chinmay; Rizwan, Muhammad
• Is Part Of: Computers & electrical engineering. Volume 97(2022)
• Publication Date: 2022-01
• Subjects: Cognitive computing -- Cyber–physical system -- Banking sector -- Suspicious transaction detection -- Quantum computing -- Machine learning; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2021.107596
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Fraud risks and threats are the critical concerns in Banking Cyber–Physical System (BCPS). Alongside the other banking frauds (i.e., forgery, altered cheques, identity theft, and impersonation), suspicious transaction detection is crucial in fraud detection. It is generally unfeasible to perform early scammer detection. Alleviating BCPS threats requires a blend of risk infiltration, sensing, and detection. A secure and robust approach is considerably required for tracking the interacting agent's provided credentials. The classical approaches provided in the literature are less competent, reliable, and accurate. Accordingly, in this paper, we provide the fastest, reliable, and efficient fraud detection approach. We use cognitive computing and quantum computing-based suspicious entity detection in the BCPS for the post-quantum era. The proposed approach achieves 97.04% of precision and 0.03% of error-rate against categorizing transactions as genuine or fraudulent. Graphical abstract: Highlights: Propose a reliable, intelligent scheme for suspicious transaction detection in a BCPS. Performs cognitive computing and quantum computing-based suspicious transaction detection. Proposed approach efficiently assists in proper and timely secure responding.