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
  • [21] Developing and Operating Artificial Intelligence Models in Trustworthy Autonomous Systems
    Martinez-Fernandez, Silverio
    Franch, Xavier
    Jedlitschka, Andreas
    Oriol, Marc
    Trendowicz, Adam
    RESEARCH CHALLENGES IN INFORMATION SCIENCE (RCIS 2021), 2021, 415 : 221 - 229
  • [22] AUTONOMOUS WIRELESS SYSTEMS WITH ARTIFICIAL INTELLIGENCE A Knowledge Management Perspective
    Gacanin, Haris
    IEEE VEHICULAR TECHNOLOGY MAGAZINE, 2019, 14 (03): : 51 - 59
  • [23] Feeling Artificial Intelligence for AI-Enabled Autonomous Systems
    Kargin, Anatolii
    Petrenko, Tetyana
    2022 IEEE GLOBAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS (GCAIOT), 2022, : 88 - 93
  • [24] Survey of RPAS Autonomous Control Systems Using Artificial Intelligence
    Aibin, Michal
    Aldiab, Motasem
    Bhavsar, Ruchi
    Lodhra, Jasleen
    Reyes, Mino
    Rezaeian, Fifi
    Saczuk, Eric
    Taer, Mahsa
    Taer, Maryam
    IEEE ACCESS, 2021, 9 : 167580 - 167591
  • [25] A user-centered explainable artificial intelligence approach for financial fraud detection
    Zhou, Ying
    Li, Haoran
    Xiao, Zhi
    Qiu, Jing
    FINANCE RESEARCH LETTERS, 2023, 58
  • [26] A New Automated Energy Meter Fraud Detection System Based on Artificial Intelligence
    Klock, Joao Pedro
    Correa, Jhonatan
    Bessa, Miguel
    Arias-Garcia, Janier
    Barboza, Felipe
    Meinertz, Carmo
    2021 XI BRAZILIAN SYMPOSIUM ON COMPUTING SYSTEMS ENGINEERING (SBESC), 2021,
  • [27] Ai in Fraud Detection: Evaluating the Efficacy of Artificial Intelligence in Preventing Financial Misconduct
    Mohan, Raja
    Boopathi, Mythili
    Ranjan, Piyush
    Najana, Madhavi
    Chaudhary, Pranav Kumar
    Chotrani, Aakash Kishore
    JOURNAL OF ELECTRICAL SYSTEMS, 2024, 20 (03) : 1332 - 1338
  • [28] Information, uncertainty and the manipulability of artificial intelligence autonomous vehicles systems
    Osorio, Antonio
    Pinto, Alberto
    INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, 2019, 130 : 40 - 46
  • [29] The Challenges and Opportunities of Artificial Intelligence for Trustworthy Robots and Autonomous Systems
    He, Hongmei
    Gray, John
    Cangelosi, Angelo
    Meng, Qinggang
    McGinnity, T. M.
    Mehnen, Jorn
    2020 THE 3RD INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTICS AND CONTROL ENGINEERING (IRCE 2020), 2020, : 68 - 74
  • [30] Connected and Autonomous Systems: Where Radar Meets Artificial Intelligence
    Cidronali, Alessandro
    IEEE MICROWAVE MAGAZINE, 2024, 25 (11) : 11 - 12