The use of automated information systems in the investigation of criminal offences
Keywords:
information systems, artificial intelligence, investigation, proceedings.
Abstract
The aim of the study was to develop recommendations for the most effective and safe use of automated information systems in the investigation of criminal offences. The study involved the following methods: anamnestic method; descriptive analysis; forecasting method. The society uses an automated information system, which is defined as an ordered complex (system) of actions designed to implement a specific information technology for the performance of specified functions, which involves personnel and a complex of automation tools. They help to create databases, which are used in the investigation of criminal offences. The following measures are proposed for increasing the efficiency and expanding the scope of automated information systems in the investigation of crimes: ensure the protection of databases from external intrusions (cyber-attacks); ensure the internal security of the data contained in the respective databases in order to prevent privacy violations; ensure the organization of specialized training for law enforcement officers; automate a number of tactical operations using information systems; develop and adapt all possible information resources and technologies for the set procedural tasks; create unified databases of forensic data at the international and national levels. This study opens up prospects for further research for the most effective protection of databases from illegal use, which will contribute to the development of this direction in international and national criminal justice.
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References
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Solovyeva, N. A., & Frantsiforov, Y. V. (2020). Specifics of Electronic and Digital Law Enforcement in Crime Investigation. (vol. 110, pp. 449–458). Cham: Springer. https://doi.org/10.1007/978-3-030-45913-0_53
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Thornton, J. (2016). Cost, Accuracy, and Subjective Fairness in Legal Information Technology: A Response to Technological Due Process Critics. 91 N.Y.U. L. Rev. 1821 Retrieved from https://heinonline.org/HOL/LandingPage?handle=hein.journals/nylr91&div=52&id=&page=
Uncovered. (2022). 20 Databases Used in Forensic Science Investigations. Retrieved from https://uncovered.com/20-databases-used-in-forensic-science-investigations/
Uzlov, D., & Strukov, V. (2017). Web-based protected geoinformation system of criminal analysis (RICAS) for analytical support for crimes investigation. In: 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T) (pp. 508-511). Kharkiv, Ukraine. https://doi.org/10.1109/INFOCOMMST.2017.8246450
Willis, J. J., Koper, C. S., & Lum, C. (2020). Technology use and constituting structures: accounting for the consequences of information technology on police organisational change. Policing and Society, 30(5), 483-501. https://doi.org/10.1080/10439463.2018.1557660
Arshad, H., Omlara, E., Oludare Abiodun, I., & Aminu, A. (2020). A semi-automated forensic investigation model for online social networks. Computers & Security, 97. https://doi.org/10.1016/j.cose.2020.101946
Black, K. (2023). What is an Automated Information System? Easytechjunkie. Retrieved from https://www.easytechjunkie.com/what-is-an-automated-information-system.htm
Bulgakova, E., Bulgakov, V., Trushchenkov, I., Vasilev, D., & Kravets, E. (2019). Big Data in Investigating and Preventing Crimes. In: A. Kravets (Ed), Big Data-driven World: Legislation Issues and Control Technologies. Studies in Systems, Decision and Control (vol. 181). Cham: Springer. https://doi.org/10.1007/978-3-030-01358-5_6
Carnaz, G., Beires Nogueira, V., Antunes, M., & Ferreira, N. (2020). An Automated System for Criminal Police Reports Analysis. (vol. 942, pp. 360–369). Cham: Springer. https://doi.org/10.1007/978-3-030-17065-3_36
Council Act of 26 July 1995 No 95/C 316/01. Drawing up the Convention based on Article K.3 of the Treaty on European Union, on the establishment of a European Police Office (Europol Convention). Official Journal of the European Communities, C 316/1. Retrieved from https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:C:1995:316:0001:0032:EN:PDF
Dawson, M. E., Crespo, M., & Brewster, S. (2013). DoD cyber technology policies to secure automated information systems. International Journal of Business Continuity and Risk Management, 4(1), 1–22. https://doi.org/10.1504/ijbcrm.2013.053089
Fisun, V. (2020). Problems of personal data protection: experience of Ukraine and other countries. Yurydychna hazeta Online, 10(716). Retrieved from https://yur-gazeta.com/publications/practice/informaciyne-pravo-telekomunikaciyi/problemi-zahistu-personalnih-danih-dosvid-ukrayini-ta-inshih-krayin.html
Haraksim, R., Galbally, J., & Beslay, L. (2019). Study on Fingermark and Palmmark Identification Technologies for their Implementation in the Schengen Information System. Luxembourg: Publication office of the European Union. Doi: 10.2760/852462
Interpol. (2022). Our 19 databases. Retrieved from https://www.interpol.int/How-we-work/Databases/Our-19-databases
Jadhav, E. B., Sankhla, M. S., & Kumar, R. (2020). Artificial Intelligence: Advancing Automation in Forensic Science & Criminal Investigation. Journal of Seybold Report, 15(8). Retrieved from https://www.researchgate.net/publication/343826071
Kalinin, M. O. (2010). Permanent protection of information systems with method of automated security and integrity control. In: Proceedings of the 3rd international conference on Security of information and networks (pp. 118-123). Association for Computing Machinery, New York. https://doi.org/10.1145/1854099.1854125
Kirilchuka, S., Reutova, V., Nalivaychenkoa, E., Shevchenkoa, E., & Yaroshenko, A. (2022). Ensuring the security of an automated information system in a regional innovation cluster. Transportation Research Procedia, 63, 607–617. Retrieved from https://acortar.link/RW4oVv
Kovacevic, A. (2020). The 5 Most Important Criminal DNA And Crime Data Sources. Smart data collective. Retrieved from https://www.smartdatacollective.com/5-important-criminal-dna-and-crime-data-sources/
Pramanik, M. I., Lau, R. Y. K., Yue, W. T., Ye, Yu., & Li, C. (2017). Big data analytics for security and criminal investigations. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7, e1208. https://doi.org/10.1002/widm.1208
Rigano, C. (2019). Using artificial intelligence to address criminal justice needs. National Institute of Justice, 280. Retrieved from https://www.cep-probation.org/wp-content/uploads/2020/11/252038.pdf
Ritchie, K. L., Cartledge, C., Growns, B., Yan, A., Wang, Y., Guo, K., Kramer, R. S. S. … White, D. (2021). Public attitudes towards the use of automatic facial recognition technology in criminal justice systems around the world. PLoS ONE, 16(10), e0258241. https://doi.org/10.1371/journal.pone.0258241
Sirant, M. (2016). Police cooperation Ukraine and the European Union – legal aspects. Bulletin of Lviv Polytechnic National University. Series: Legal Sciences, 850, 353-360. Retrieved from http://nbuv.gov.ua/UJRN/vnulpurn_2016_850_54
Smith, M., & Miller, S. (2022). The ethical application of biometric facial recognition technology. AI & SOCIETY, 37, 167–175. https://doi.org/10.1007/s00146-021-01199-9
Smith, M., Mann, M., & Urbas, G. (2018). Biometrics, Crime and Security. London: Routledge, https://doi.org/10.4324/9781315182056
Solovyeva, N. A., & Frantsiforov, Y. V. (2020). Specifics of Electronic and Digital Law Enforcement in Crime Investigation. (vol. 110, pp. 449–458). Cham: Springer. https://doi.org/10.1007/978-3-030-45913-0_53
Thompson, T. (2010). Crime software may help police predict violent offences. The Guardian. Retrieved from http://www.theguardian.com/uk/2010/jul/25/police-software-crime-prediction
Thornton, J. (2016). Cost, Accuracy, and Subjective Fairness in Legal Information Technology: A Response to Technological Due Process Critics. 91 N.Y.U. L. Rev. 1821 Retrieved from https://heinonline.org/HOL/LandingPage?handle=hein.journals/nylr91&div=52&id=&page=
Uncovered. (2022). 20 Databases Used in Forensic Science Investigations. Retrieved from https://uncovered.com/20-databases-used-in-forensic-science-investigations/
Uzlov, D., & Strukov, V. (2017). Web-based protected geoinformation system of criminal analysis (RICAS) for analytical support for crimes investigation. In: 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T) (pp. 508-511). Kharkiv, Ukraine. https://doi.org/10.1109/INFOCOMMST.2017.8246450
Willis, J. J., Koper, C. S., & Lum, C. (2020). Technology use and constituting structures: accounting for the consequences of information technology on police organisational change. Policing and Society, 30(5), 483-501. https://doi.org/10.1080/10439463.2018.1557660
Published
2023-02-28
How to Cite
Kaduk, S., Shulha, A., Svoboda, I., Varyvoda, I., & Mykytyn, Y. (2023). The use of automated information systems in the investigation of criminal offences. Amazonia Investiga, 12(61), 307-316. https://doi.org/10.34069/AI/2023.61.01.31
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