DEVELOPMENT OF APPLIED ONTOLOGY FOR THE ANALYSIS OF DIGITAL CRIMINAL CRIME
DOI:
https://doi.org/10.15588/1607-3274-2023-4-17Keywords:
ontology, digital forensic, digital crime, digital evidenceAbstract
Context. A feature of the modern digital world is that crime is often committed thanks to the latest computer technologies, and the work of law enforcement agencies faces a number of complex challenges in the digital environment. The development of information technology and Internet communications creates new opportunities for criminals who use digital traces and evidence to commit crimes, which complicates the process of identifying and tracking them.
Objective. Development of an applied ontology for a system for analyzing a digital criminal offense, which will effectively analyze, process and interpret a large amount of digital data. It will help to cope with the complex task of processing digital data, and will also help automate the process of discovering new knowledge.
Methods. To build an ontological model as a means of reflecting knowledge about digital crime, information was collected on existing international and domestic classifications. The needs and requirements that must be satisfied by the developed ontology were also analyzed. The creation of an ontological model that reflects the basic concepts, relationships in the field of digital criminal offense was carried out in accordance with a recognized ontological analysis of a specialized subject area.
Results. An applied ontology contains the definition of entities, properties, classes, subclasses, etc., as well as the creation of semantic relationships between them. At the center of the semantics is the Digital Crime class, the problem area of which is complemented by the interrelated classes Intruder, Digital evidence, Types of Crime, and Criminal liability. Such characteristics as motive, type of crime, method of commission, classification signs of digital traces and types of crime, as well as other individual information were assigned to the attributes of the corresponding classes. An ontological model was implemented in OWL using the Protégé software tool. A feature of the implementation of the applied ontology was the creation of SWRL rules for automatically filling in additional links between a class instance. Manual and automatic verification of the ontology showed the integrity, consistency, a high degree of correctness and adequacy of the model. The bugs found were usually related to technical aspects and semantic inconsistencies, which were corrected during further development iterations.
Conclusions. The research confirmed the effectiveness of the developed applied ontology for the analysis of digital criminality, providing more accurate and faster results compared to traditional approaches.
References
Pro zareyestrovani kryminalni pravoporushennya ta rezultaty yikh dosudovoho rozsliduvannya (2023) In: ofis holovnoho prokurora. https://gp.gov.ua/ua/posts/pro-zareyestrovanikriminalni-pravoporushennya-ta-rezultati-yih-dosudovogorozsliduvannya-2. Accessed 20 Aug 2023
Barn R., Barn B. An ontological representation of a taxonomy for cybercrime, Twenty-Fourth European Conference on Information Systems (ECIS). İstanbul, Turkey, 2016. Access mode: https://core.ac.uk/download/pdf/42490758.pdf
Vlasenko L., Lutska N., Zaiets N., Korobiichuk I., Hrybkov S. Core Ontology for Describing Production Equipment According to Intelligent Production, Applied System Innovation, 2022, Vol. 5, Issue 5, pp. 98–111. DOI: 10.3390/asi5050098
Vlasenko L. O., Lutska N. M., Zaiets N. A., Shyshak A. V., Savchuk O. V. Domain ontology development for condition monitoring system of industrial control equipment and devices, Radio Electronics, Computer Science, Control, 2022, Vol. 1, pp. 157–166. DOI: 10.15588/1607-3274-2022-1-16
Donalds C., Osei-Bryson K. M. Toward a cybercrime classification ontology: A knowledge-based approach, Computers in Human Behavior, 2019, Vol. 92, pp. 403–418. DOI: 10.1016/j.chb.2018.11.039
Sikos L. F. AI in digital forensics: Ontology engineering for cybercrime investigations. Wiley Interdisciplinary Reviews: Forensic Science, 2020, Vol. 3, Issue 3, pp. 1–11. DOI: 10.1002/wfs2.1394
Karanasios S., Thakker D., Lau L., Allen D., Dimitrova V., Norman A. Making sense of digital traces: An activity theory driven ontological approach, Journal of the American Society for Information Science and Technology, 2013, Vol. 64, Issue 12, pp. 2452–2467. DOI: 10.1002/asi.22935
Brady O., Overill R., Keppens J. Addressing the increasing volume and variety of digital evidence using an ontology. 2014 IEEE joint intelligence and security informatics conference. IEEE, 2014. pp. 176–183. DOI: 10.1109/JISIC.2014.34
Michel M. C., Carvalho M., Crawford H., Esterline A. C. Cyber identity: Salient trait ontology and computational framework to aid in solving cybercrime, 2018 17th IEEE International Conference on Trust, Security and Privacy In Computing and Communications/12th IEEE International Conference on Big Data Science And Engineering (TrustCom/BigDataSE), IEEE, 2018, pp. 1242–1249. DOI: 10.1109/TrustCom/BigDataSE.2018.00171
Alzaabi M., Jones A., Martin T. A. An Ontology-Based Forensic Analysis Tool. Proceedings of the 2013 Annual ADFSL Conference on Digital Forensics, Security and Law, 2013, pp. 121–136. Access mode: https://commons.erau.edu/adfsl/2013/wednesday/5
Akremi A., Sriti M.-F., Sallay H., Rouached M., Ontologybased smart sound digital forensics analysis for web services, International Journal of Web Services Research, 2019, Vol. 16, № 1, 70–92. DOI: 10.4018/IJWSR.2019010104
Alzaabi M., Ontology-Based Forensic Analysis of Mobile Devices, Proceedings of the 20th IEEE International Conference on Electronics, Circuits and Systems, IEEE, 2013, pp. 64–68. DOI: 10.1109/ICECS.2013.6815346
Park H., Cho S., Kwon H. Cyber Forensics Ontology for Cyber Criminal Investigation. Forensics in Telecommunications, Information and Multimedia, LNICST, 2009, Vol. 8, pp. 160–165. DOI: 10.1007/978-3-642-02312-5_18
Naidyon Ya. Ponyattya ta klasyfikatsiya virtualnykh slidiv kiberzlochyniv, Pidpryyemnytstvo, hospodarstvo i pravo, 2019, 5, pp. 304–307. DOI: 10.32849/2663-5313/2019.5.56
Lysenko S. M., et al. Rezilientnist kompiuternykh system v umovakh kiberzahroz: Ontolohiia ta taksonomiia, Radioelektronni i kompiuterni systemy, 2020, No. 1, pp. 17–28. DOI: 10.32620/reks.2020.1.02
Maskun M., Achmad A., Naswar N., Assidiq H., Syafira A., Napang M., Hendrapati M. Qualifying Cyber Crime as a Crime of Aggression in International Law, Cybercrime under International Law, 2020, – Vol. 13, № 2, pp. 397–418. DOI: 10.14330/jeail.2020.13.2.08
Uma M., Padmavathi G. A survey on various cyber attacks and their classification, Int. J. Netw. Secur., 2013, Vol. 15, №5, pp. 390–396. DOI:10.6633/IJNS.201309.15(5).09
Chandra A., Snowe M. J. A taxonomy of cybercrime: Theory and design, International Journal of Accounting Information Systems, 2020, Vol. 38, pp. 100467. DOI: 10.1016/j.accinf.2020.100467
Harmandeep S. B., Kumar G. Cybercrimes: A proposed taxonomy and challenges, Journal of Computer Networks and Communications, 2018, Vol. 11. DOI: 10.1155/2018/1798659
Goni O. Cyber Crime and Its Classification, Int. J. of Electronics Engineering and Applications, 2022, Vol. 10, № 1, pp. 1–17, DOI: 10.30696/IJEEA.X.I.2021.01-17In
Kryminalnyi kodeks Ukrainy (2001) In: Verkhovna Rada Ukrainy. Zakonodavstvo Ukrainy. https://zakon.rada.gov.ua/laws/show/2341-14. Accessed 20 Aug 2023
Themis. Ontology testing. https://themis.linkeddata.es/index.html. Accessed 20 Aug 2023
Lutska N., Vlasenko L., Ladanyuk A., Zaiets N., Korobiichuk I. Ontological Support System of Managerial Decision-Making of Production Tasks for a Food Enterprise, Machinery & Energetics, 2022, Vol. 13, № 3, pp. 53–61. DOI: 10.31548/machenergy.13(3).2022.53-61
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 L. O. Vlasenko, N. M Lutska, N. A. Zaiets, T. V. Savchenko, A. A. Rudenskiy
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Creative Commons Licensing Notifications in the Copyright Notices
The journal allows the authors to hold the copyright without restrictions and to retain publishing rights without restrictions.
The journal allows readers to read, download, copy, distribute, print, search, or link to the full texts of its articles.
The journal allows to reuse and remixing of its content, in accordance with a Creative Commons license СС BY -SA.
Authors who publish with this journal agree to the following terms:
-
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License CC BY-SA that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
-
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
-
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
