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Artificial Intelligence and Crime Detection: A Critical Review | ||
| Journal of Cyberspace Studies | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 30 شهریور 1404 اصل مقاله (326.75 K) | ||
| نوع مقاله: Original article | ||
| شناسه دیجیتال (DOI): 10.22059/jcss.2025.402206.1179 | ||
| نویسندگان | ||
| Karim Salehi1؛ Simin Habib Zadeh Khiyaban* 2؛ Shoaib Sabbar3 | ||
| 1Department of Law, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran. | ||
| 2Department of Public Administration, Faculty of Accounting and Management, Allameh Tabataba’i University, Tehran, Iran. | ||
| 3Department of International Commercial Law, Faculty of Law, Azad University, Tehran. Iran. | ||
| چکیده | ||
| Background: Since the advent of modern policing, technological innovations in communication and information management have significantly shaped investigative practices and crime detection strategies. Aims: The current research study explores the transformative role of Artificial Intelligence in modern crime detection and prevention across diverse domains including cybercrime, environmental crime, financial fraud, and urban surveillance. Methodology: Employing a qualitative meta-synthesis methodology, the research critically examines peer-reviewed literature published between the years 2015 and 2025 to identify emerging trends, technological innovations, and socio-legal implications associated with AI-driven policing. Findings: The key findings highlight the integration of machine learning, computer vision, and natural language processing techniques into the predictive and real-time law enforcement systems. These technologies have demonstrably enhanced the accuracy, efficiency, and responsiveness of crime prevention strategies. However, the current study also reveals significant challenges, including algorithmic bias, lack of transparency, and inadequate regulatory oversight, particularly in socially stratified or underregulated contexts. Conclusion: The current article underscores the necessity of embedding explainability, accountability, and human oversight into Artificial Intelligence systems to ensure the ethical and equitable implementation of AI-driven policing systems. | ||
| کلیدواژه‌ها | ||
| artificial intelligence؛ crime prevention؛ predictive policing؛ algorithmic accountability؛ surveillance ethics | ||
| مراجع | ||
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AlSuwaidi, H.A.; Harous, S.; Serhani, M.A. (2024). “Review of visual AI applications in smart surveillance for crime detection and prevention: A survey”. 4th International Conference on Distributed Sensing and Intelligent Systems (ICDSIS 2023). https://doi.org/10.1049/icp.2024.0502.
Apene O.Z.; Blamah, N.V.; & Aimufua, G.I.O. (2024). “Advancements in crime prevention and detection: From traditional approaches to artificial intelligence solutions”. European Journal of Applied Science, Engineering and Technology. 2(2): 285-297. https://doi.org/10.59324/ejaset.2024.2(2).20.
Babuta, A.; & Oswald, M. (2020). Data Analytics and Algorithms in Policing in England and Wales. Royal United Services Institute. https://static.rusi.org/rusi_pub_165_2020_01_algorithmic_policing_babuta_final_web_copy.pdf.
Bagonza, J.K.; Nakayenga, H.; & Zimbe, I. (2024). “Leveraging AI for real time crime prediction, disaster response optimization and threat detection to improve public safety and emergency management in the US”. World Journal of Advanced Research and Reviews. 23(3): Article 2835. https://doi.org/10.30574/WJARR.2024.23.3.2835.
Basthikodi, M.; Vidya, B.; Pinto, E.M.; Basith, M.; & Rao, S.A. (2024). “AI based automated framework for crime detection and crowd management”. In 2024 Second International Conference on Advances in Information Technology (ICAIT). IEEE. https://doi.org/10.1109/ICAIT61638.2024.10690527.
Bertrand, A.; Eagan, J.R.; Maxwell, W.; & Brand, J. (2024). “AI is entering regulated territory: Understanding the supervisors' perspective for model justifiability in financial crime detection”. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems. Article 480: 1-21. https://doi.org/10.1145/3613904.3642326.
Black, A. (2023). “AI and democratic equality: how surveillance capitalism and computational propaganda threaten democracy”. In International Conference on Bridging the Gap between AI and Reality (pp. 333-347). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-73741-1_21.
Brantingham, P.J.; Valasik, M. & Mohler, G.O. (2018). “Does predictive policing lead to biased arrests? Results from a randomized controlled trial”. Statistics and Public Policy. 5(1): 1-6. https://doi.org/10.1080/2330443X.2018.1438940.
Butt, U.M.; Letchmunan, S.; Hassan, F.H.; Ali, M.; Baqir, A.; & Koh, T.W. (2021). “Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities”. IEEE Access. 9: 47516-47529. https://doi.org/10.1109/ACCESS.2021.3068306.
Ersöz, F.; Ersöz, T.; Marcelloni, F.; & Ruffini, F. (2025). “Artificial Intelligence in crime prediction: A survey with a focus on explainability”. IEEE Access. 13: 59646–59674. https://doi.org/10.1109/ACCESS.2025.3553934.
Fernandez-Basso, C.; Gutiérrez-Batista, K.; Gómez-Romero, J.; Ruiz, M.D.; & Martin-Bautista, M.J. (2025). “An AI knowledge-based system for police assistance in crime investigation”. Expert Systems. 42(1): e13524. https://doi.org/10.1111/exsy.13524.
Gandal, J.R.; Gandal, S.J.; & Suryavanshi, M. (2024). “Analysis of object detection, prediction, and prevention AI and ML algorithms for enhancing crime surveillance videos”. In 2024 IEEE 9th International Conference for Convergence in Technology (I2CT). IEEE. https://doi.org/10.1109/I2CT61223.2024.10544214.
Gopichand, G.; Vijayakumar; & Pasupuleti, N.S. (2021). “On-road crime detection using artificial intelligence”. In Favorskaya, M.N.; Mekhilef, S.; Pandey, R.K.; & Singh, N. (Eds.). Innovations in Electrical and Electronic Engineering (pp. 423-432). Springer. https://doi.org/10.1007/978-981-15-4692-1_32.
Iqbal, N.; Hassan, A.; & Waheed, T. (2025). “AI-driven crime prediction: A systematic literature review”. Journal of Computational Social Science. 8: 53. https://doi.org/10.1007/s42001-025-00373-z.
Kanwal, S.; Iftikhar, S.; Munir, R.; Ahmad, M.; & Waheed, A. (2025). “Role of artificial intelligence in crime detection and control: Enhancing policing strategies and effectiveness”. Journal of Social Signs Review. 3(07): 243-255. https://www.socialsignsreivew.com/index.php/12/article/view/324.
Kaushik, A.; Paprunia, D.; Wangde, I.; Jain, S.; Deepak, S.; & Sankhe, M. (2025). “Advanced AI-Based Detection and Tracking System (ADTS) for crime prevention and identification in real-time surveillance”. In 2025 International Conference on Computing Technologies (ICOCT). IEEE. https://doi.org/10.1109/ICOCT64433.2025.11118424.
Leukfeldt, R.; & Holt ,T.J. (2020). The Human Factor in Cybercrime. London, Routledge. https://doi.org/10.4324/9780429460593.
Manning, P.K. (2008). The Technology of Policing: Crime Mapping, Information Technology, and the Rationality of Crime Control. NYU Press. http://ndl.ethernet.edu.et/bitstream/123456789/14252/1/81.pdf.
McCue, C. (2020). Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis. 2nd ed. Butterworth-Heinemann. http://repo.darmajaya.ac.id/4009/1/Data%20Mining%20and%20Predictive%20Analysis%2C%20Second%20Edition_%20Intelligence%20Gathering%20and%20Crime%20Analysis%20%28%20PDFDrive%20%29.pdf.
Meena M.; & Joshi, A. (2023). “AI policing in criminal justice: Methods & concerns in crime detection and prevention in India”. NFSU Journal of Law and Artificial Intelligence. 2(1). https://doi.org/10.62995/jlai1220250812.
Natarajan, R.; Mahadev, N.; Gupta, S.K.; & Alfurhood, B.S. (2024). “An investigation of crime detection using Artificial Intelligence and face sketch synthesis”. Journal of Applied Security Research. 19(4): 542-559. https://doi.org/10.1080/19361610.2024.2302237.
Rahmatian. F.; & Sharajsharifi, M. (2022). “Reimagining MBA education in the age of artificial intelligence: A meta-synthesis”. Socio-Spatial Studies. 6(1). https://doi.org/10.22034/soc.2022.223610.
Rahmatian, F.; & Sharajsharifi, M. (2021). “Artificial intelligence in MBA education: Perceptions, ethics, and readiness among Iranian graduates”. Socio-Spatial Studies. 5(1). https://doi.org/10.22034/soc.2021.223600.
Sharma, P.; Prakash, A.S.; & Malhotra, A. (2024). “Application of advanced AI algorithms for fintech crime detection”. In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE. https://doi.org/10.1109/ICCCNT61001.2024.10725857.
Shoeibi, N.; Shoeibi, N.; Hernández, G.; Chamoso, P.; & Corchado, J.M. (2021). “AI-crime hunter: An AI mixture of experts for crime discovery on Twitter”. Electronics. 10(24): 3081. https://doi.org/10.3390/electronics10243081.
Singh, S. (2024). “AI in environmental crime detection: A paradigm shift in criminal law”. Conference: Environmental Law: Issues and Emerging Challenges. SSRN. https://ssrn.com/abstract=5123120.
Tayal, D.K.; Jain, A.; Arora, S.; Agarwal, S.; Gupta, T.; & Tyagi, N. (2015). “Crime detection and criminal identification in India using data mining techniques”. AI & Society. 30: 117-127. https://doi.org/10.1007/s00146-014-0539-6. | ||
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