Keywords
Offence
Crime
Military Operations
Criminal Activity
Crime Rate
FMEA Model
Risk Prediction
How to Cite
Abstract
Military operations cause various violations in the state security system, including an increased criminal activity. This requires improved and innovative response to offences and crimes, which include forensic computer simulation of offences. The aim of this work is to determine an approach to the development of a forensic computer model of offences in the context of military operations and to assess its potential advantages. The research involved the method of statistical observation, the rating method, the analysis of risks and potential failures using the FMEA model. The conducted research revealed an increased crime rate in Ukraine after the full-scale invasion. The increased number of particularly serious crimes by almost 9 times requires special attention. This gave grounds to propose the directions of application of the method of forensic computer simulation of offences — forecasting and analysis of crimes, geo-informational simulation, etc. An algorithm for the development of a forensic computer model for predicting terrorist acts in the context of a military conflict is proposed. It is noted that the effectiveness of this model depends on the correct identification and assessment of possible risks for the security system, which is proposed to be carried out using the FMEA model. The application of the FMEA model for predicting terrorist acts is the novelty of the study.
References
AL-DHAQM, A., ABD RAZAK, S., OTHMAN, S. H., ALI, A., GHALEB, F. A., ROSMAN, A. S., MARNI, N. Database forensic investigation process models: A review. IEEE Access, v. 8, p. 48477-48490, 2020. https://doi.org/10.1109/ACCESS.2020.2976885
BABUTA, A., OSWALD, M. Data analytics and algorithms in policing in England and Wales: Towards a new policy framework. 2020. Available at: http://nrl.northumbria.ac.uk/id/eprint/42903 Accessed on: 05 Nov. 2023.
BEN HASSEN, T., EL BILALI, H. Impacts of the Russia-Ukraine war on global food security: towards more sustainable and resilient food systems? Foods, v. 11, n. 15, p. 2301, 2022. https://doi.org/10.3390/foods11152301
BOUBAKER, S., GOODELL, J. W., PANDEY, D. K., KUMARI, V. Heterogeneous impacts of wars on global equity markets: Evidence from the invasion of Ukraine. Finance Research Letters, v. 48, p. 102934, 2022. https://doi.org/10.1016/j.frl.2022.102934
CASEY, E. The chequered past and risky future of digital forensics. Australian Journal of Forensic Sciences, v. 51, n. 6, p. 649-664, 2019. https://doi.org/10.1080/00450618.2018.1554090
CHYRENKO, M. Another side of the coin: how the war affected the crime rate. 2023. Available at: https://www.dsnews.ua/ukr/politics/shche-odin-bik-medali-yak-viyna-vplinula-na-riven-zlochinnosti-27022023-475107 Accessed on: 05 Nov. 2023.
DALY, S. Z., PALER, L., SAMII, C. Wartime ties and the social logic of crime. Journal of Peace Research, v. 57, n. 4, p. 536-550, 2020. https://doi.org/10.1177/0022343319897098
DASAKLIS, T. K., CASINO, F., PATSAKIS, C. SoK: Blockchain solutions for forensics. In Technology Development for Security Practitioners. Cham: Springer, 2021, p. 21-40. https://doi.org/10.1007/978-3-030-69460-9_2
FREEMAN, L. Digital evidence and war crimes prosecutions: the impact of digital technologies on international criminal investigations and trials. Fordham Int'l LJ, v. 41, p. 283, 2017. Available at: https://ir.lawnet.fordham.edu/ilj/vol41/iss2/1 Accessed on: 05 Nov. 2023.
GOSTIN, L. O., RUBENSTEIN, L. S. Attacks on health care in the war in Ukraine: International law and the need for accountability. JAMA, v. 327, n. 16, p. 1541-1542, 2022. https://doi.org/10.1001/jama.2022.6045
HO, H., KO, R., MAZEROLLE, L. Situational Crime Prevention (SCP) techniques to prevent and control cybercrimes: A focused systematic review. Computers & Security, v. 115, p. 102611, 2022. https://doi.org/10.1016/j.cose.2022.102611
HOANG, N. D., HUYNH, T. C., TRAN, V. D. Computer vision-based patched and unpatched pothole classification using machine learning approach optimized by forensic-based investigation metaheuristic. Complexity, v. 2021, p. 1-17, 2021. https://doi.org/10.1155/2021/3511375
JAFARI, F., SATTI, R. S. Comparative analysis of digital forensic models. Journal of Advances in Computer Networks, v. 3, n. 1, p. 82-86, 2015. https://doi.org/10.7763/JACN.2015.V3.146
JARRETT, A., CHOO, K. K. R. The impact of automation and artificial intelligence on digital forensics. Wiley Interdisciplinary Reviews: Forensic Science, v. 3, n. 6, p. e1418, 2021. https://doi.org/10.1002/wfs2.1418
JIN, G., WANG, Q., ZHU, C., FENG, Y., HUANG, J., ZHOU, J. Addressing crime situation forecasting task with temporal graph convolutional neural network approach. In: 2020 12th International Conference on Measuring Technology and Mechatronics Automation. IEEE: 2020, p. 474-478. https://doi.org/10.1109/ICMTMA50254.2020.00108
KOENIG, A., IRVING, E., MCDERMOTT, Y., MURRAY, D. New technologies and the investigation of international crimes: An introduction. Journal of International Criminal Justice, v. 19, n. 1, p. 1-7, 2021. https://doi.org/10.1093/jicj/mqab040
KOLLA, V. R. K. A Comparative Analysis of OS Forensics Tools. International Journal of Research in IT and Management, v. 12, n. 4, 2022. Available at: https://ssrn.com/abstract=4413730 Accessed on: 05 Nov. 2023.
KORNIIENKO, V. V. Forensic 3D modeling of the scene. In: Theoretical issues of jurisprudence and problems of law enforcement: challenges of the 21st century. Theses of the reports of the participants of the 3rd All-Ukrainian Scientific and Practical Conference. Public Policy and Social Sciences Research Institute, 2020, p. 165-167. Available at: https://dspace.univd.edu.ua/server/api/core/bitstreams/e2172522-77cc-48a2-bcb2-aa47fec76578/content#page=165 Accessed on: 05 Nov. 2023.
KUMAR, S., PATHAK, S. K., SINGH, J. A Comprehensive Study of XSS Attack and the Digital Forensic Models to Gather the Evidence. ECS Transactions, v. 107, n. 1, p. 7153, 2022. https://doi.org/10.1149/10701.7153ecst
MBAH, R. E., WASUM, D. F. Russian-Ukraine 2022 War: A review of the economic impact of Russian-Ukraine crisis on the USA, UK, Canada, and Europe. Advances in Social Sciences Research Journal, v. 9, n. 3, p. 144-153, 2022. https://doi.org/10.14738/assrj.93.12005.
MILIVOJEVIC, S., RADULSKI, E. M. The ‘future Internet’ and crime: towards a criminology of the Internet of Things. Current Issues in Criminal Justice, v. 32, n. 2, p. 193-207, 2020. https://doi.org/10.1080/10345329.2020.1733452
NUMBEO. Crime Index by Country 2023. 2023. Available at: https://www.numbeo.com/crime/rankings_by_country.jsp Accessed on: 05 Nov. 2023.
OZKAN, T. Criminology in the age of data explosion: New directions. The Social Science Journal, v. 56, n. 2, p. 208-219, 2019. https://doi.org/10.1016/j.soscij.2018.10.010
PODOBNYI, O. O., SLATVINSKA, V. M. Main tasks of informatization of law enforcement activities. Juridical Scientific and Electronic Journal, v. 9, p. 180-182, 2021. https://doi.org/10.32782/2524-0374/2021-9/43
PRATHAP, B. R. Geospatial crime analysis and forecasting with machine learning techniques. In: Artificial intelligence and machine learning for EDGE computing. Academic Press, 2022, p. 87-102. https://doi.org/10.1016/B978-0-12-824054-0.00008-3
RAWTANI, D., GUPTA, G., KHATRI, N., RAO, P. K., HUSSAIN, C. M. Environmental damages due to war in Ukraine: A perspective. Science of the Total Environment, v. 850, p. 157932, 2022. https://doi.org/10.1016/j.scitotenv.2022.157932
REN, L., ZHAO, J. S., HE, N. P. Broken windows theory and citizen engagement in crime prevention. Justice quarterly, v. 36, n. 1, p. 1-30, 2019. https://doi.org/10.1080/07418825.2017.1374434
SHUKLA, S., JAIN, P. K., BABU, C. R., PAMULA, R. A multivariate regression model for identifying, analyzing and predicting crimes. Wireless Personal Communications, v. 113, p. 2447-2461, 2020. https://doi.org/10.1007/s11277-020-07335-w
SOKURENKO, V. V. Peculiarities of the use of information technologies in forensics. In: Application of information technologies in law enforcement activities: materials of the Round Table. Kharkiv: KhNUVS, 2022, p. 8–12. Available at: http://dspace.univd.edu.ua/xmlui/handle/123456789/15146 Accessed on: 05 Nov. 2023.
XU, Z., CHENG, C., SUGUMARAN, V. Big data analytics of crime prevention and control based on image processing upon cloud computing. Journal of Surveillance, Security and Safety, v. 1, p. 16-33, 2020. https://doi.org/10.20517/jsss.2020.04
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