Autonomous Artificial Intelligence Systems for Fraud Detection and Forensics in Dark Web Environments

被引:0
|
作者
Rawat R. [1 ]
Oki O.A. [2 ]
Chakrawarti R.K. [3 ]
Adekunle T.S. [4 ]
Lukose J.M. [5 ]
Ajagbe S.A. [6 ]
机构
[1] Department of Computer Architecture and Communications, University of Extremadura, Badajoz
[2] Department of Information Technology, East London Walter Sisulu University
[3] Department of Computer Science and Engineering, Sushila Devi Bansal College, Bansal Group of Institutions, Indore
[4] Department of Information Technology, Walter Sisulu University
[5] Department of Computer & Industrial Production Engineering, First Technical University, Ibadan
来源
Informatica (Slovenia) | 2023年 / 47卷 / 09期
关键词
artificial intelligence; crime; cyber terrorism; cyberattack; forensics; IoT;
D O I
10.31449/INF.V46I9.4538
中图分类号
学科分类号
摘要
Artificial Intelligence (AI) influenced technical aspects of research for generating automated intelligent behaviors covering divergent domains but has shown appreciable results when used in cyber forensic technology for crime analysis and detection. AI experts warned about possible security risks associated with algorithms and training data, as AI inherits computing features dealing with IoT-based Smart applications and autonomous transportation, and may be found to be susceptible to vulnerability and threats. The present work discusses models for analyzing terrorists related information and categorizing malicious events by covering the literature review on security risks and AI-related criminality by presenting a taxonomy of criminal behavior and signatures covering tools and criminal targets used in fraudulent activities using AI features by digital forensic techniques. We've also shown how AI may make existing crimes more potent, and that new sorts of crimes could emerge that haven't been identified previously. This study has presented a systematic structure for AI crime and dealing strategies. Furthermore, we have proposed AI forensics, a unique strategy for combating AI crime. We discovered that several concepts of DF are still not preferred in AI-based forensics after conducting a comparative examination of forensics. © 2023 Slovene Society Informatika. All rights reserved.
引用
收藏
页码:51 / 62
页数:11
相关论文
共 50 条
  • [1] Fraud detection and prevention in Smart card based environments using artificial intelligence
    Malek, Wael William Zakhari
    Mayes, Keith
    Markantonakis, Kostas
    SMART CARD RESEARCH AND ADVANCED APPLICATIONS, PROCEEDINGS, 2008, 5189 : 118 - 132
  • [2] Financial Fraud Detection Through Artificial Intelligence
    Rodriguez-Aguilar, Roman
    Marmolejo-Saucedo, Jose A.
    Vasant, Pandian
    Litvinchev, Igor
    ARTIFICIAL INTELLIGENCE AND APPLIED MATHEMATICS IN ENGINEERING PROBLEMS, 2020, 43 : 57 - 72
  • [3] A New Approach for Fraud Detection with Artificial Intelligence
    Erdogan, Ipek
    Kurto, Orhan
    Kurt, Alican
    Bahtiyar, Serif
    2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2020,
  • [4] Artificial Intelligence as the basis of autonomous systems
    Künstliche Intelligenz als Grundlage autonomer Systeme
    Wahlster, Wolfgang (wahlster@dfki.de), 2017, Springer Verlag (40)
  • [5] Food fraud detection using explainable artificial intelligence
    Buyuktepe, Okan
    Catal, Cagatay
    Kar, Gorkem
    Bouzembrak, Yamine
    Marvin, Hans
    Gavai, Anand
    EXPERT SYSTEMS, 2025, 42 (01)
  • [6] Artificial Intelligence as a Game Changer in Fraud Detection? - A qualitative Analysis
    Reichelt, Valentin
    BETRIEBSWIRTSCHAFTLICHE FORSCHUNG UND PRAXIS, 2023, 75 (04):
  • [7] Fire Detection and Spatial Localization Approach for Autonomous Suppression Systems Based on Artificial Intelligence
    Latif, Afsah
    Chung, Hyun
    FIRE TECHNOLOGY, 2023, 59 (05) : 2621 - 2644
  • [8] Fire Detection and Spatial Localization Approach for Autonomous Suppression Systems Based on Artificial Intelligence
    Afsah Latif
    Hyun Chung
    Fire Technology, 2023, 59 : 2621 - 2644
  • [9] Formalization of Methods for the Development of Autonomous Artificial Intelligence Systems
    Zgurovsky, M. Z.
    Kasyanov, P. O.
    Levenchuk, L. B.
    CYBERNETICS AND SYSTEMS ANALYSIS, 2023, 59 (05) : 763 - 771
  • [10] Artificial Intelligence, Autonomous Systems and Robotics: Legal Innovations
    Rault, Raphael
    Trentesaux, Damien
    SERVICE ORIENTATION IN HOLONIC AND MULTI-AGENT MANUFACTURING, 2018, 762 : 1 - 9