ISSN 2410-3594
e-ISSN 2786-7382
UDC 34; 159.9
Scientific Journal of the National Academy of Internal Affairs
- computer data; protocol; mobile terminal; hardware and software complex; pre-trial investigation; specialist; special knowledge
- https://doi.org/10.56215/naia-herald/2.2023.52
- Pages 52-60
The relevance of the study is substantiated by the need to develop a system for procedural registration of information (statements) withdrawn from a mobile phone using hardware and software complexes, the content of which proves the involvement of a person in the commission of a criminal offence, since such a documentation mechanism has not been developed in practice. The purpose of the study was to highlight theoretical and applied approaches to the legal support of investigators’ actions to extract information from a mobile phone found at the incident scene. In accordance with the set goal and specifics of the subject of research, a set of the following methods was applied: formal logical, system and structural, hermeneutical, modelling, and generalisation. The study considers the actions of the investigator during the pre-trial investigation of criminal offences, when a cellular phone (mobile communication device) was found at the incident scene, which makes it necessary to use special knowledge. The profile and qualification of a specialist who needs to be involved in the inspection of a mobile phone are determined depending on the purpose and objectives of the investigative (search) action, established primary data on the nature of a criminal offense. A procedure for obtaining information (computer data) from a cellular phone (mobile communication device) is proposed, which provides for the creation of an “image”/electronic report of available information, which is recorded on a digital medium in the form of a file, fixed with an electronic label as a checksum. The practical value of the study lies in the procedural solution of the issue of extracting information (statements) from mobile phones, which is important during pre-trial investigation and documentation of digital information (computer data)
References
[1] Al-Faaruuq, M.S., & Priambodo, D.F. (2022). IOS digital evidence comparison of instant messaging apps. In International conference of science and information technology in smart administration (ICSINTESA) (pp. 83-88). New York: Institute for Electrical and Electronics Engineers. doi: 10.1109/ ICSINTESA56431.2022.10041620.
[2] Bowling, H., Seigfried‐Spellar, K., Karabiyik, U., & Rogers, M. (2023). We are meeting on Microsoft Teams: Forensic analysis in Windows, Android, and iOS operating systems. Journal of Forensic Sciences, 68(2), 434-460. doi: 10.1111/1556-4029.15208
[3] Dorai, G., Houshmand, S., & Baggili, I. (2018). I know what you did last summer: Your smart home internet of things and your iPhone forensically ratting you out. In ARES 2018: Proceedings of the 13th international conference on availability, reliability and security (pp. 1-10). New York: Association for Computing Machinery. doi: 10.1145/3230833.3232814.
[4] Fukami, A., Stoykova, R., & Geradts, Z. (2021). A new model for forensic data extraction from encrypted mobile devices. Forensic Science International: Digital Investigation, 38, article number 301169. doi: 10.1016/j.fsidi.2021.301169.
[5] Hutsaliuk, M.V., & Antoniuk, P.Ye. (2021). The essence of digital information a source of evidence in criminal proceedings. Forensic Herald, 33(1), 37-49. doi: 10.37025/1992-4437/2020-33-1-37.
[6] Idris, I., Alhassan, J.K., Waziri, V.O., & Majigi, M.U. (2016). SIM cards forensic capability and evaluation of extraction tools. In International conference on information and communication technology and its applications (ICTA 2016) (pp. 75-81). Minna: Federal University of Technology.
[7] Johnson, H., Volk, K., Serafin, R., Grajeda, C., & Baggili, I. (2022). Alt-tech social forensics: Forensic analysis of alternative social networking applications. Forensic Science International: Digital Investigation, 42, article number 301406. doi: 10.1016/j.fsidi.2022.301406.
[8] Karthikeyan, P., Pande, H.M., & Sarveshwaran, V. (Eds.). (2023). Artificial intelligence and blockchain in digital forensics. New York: River Publishers. doi: 10.1201/9781003374671.
[9] Kayabaş, H., & Tuna, G. (2023). Cyber wars and cyber threats against mobile devices: Analysis of mobile devices. In Handbook of research on war policies, strategies, and cyber wars (pp. 85-107). doi: 10.4018/978- 1-6684-6741-1.ch005.
[10] Keim, Y., Hutchinson, S., Shrivastava, A., & Karabiyik, U. (2022). Forensic analysis of TikTok alternatives on android and iOS devices: Byte, dubsmash, and triller. Electronics, 11(18), article number 2972. doi: 10.3390/electronics11182972.
[11] Kobets, M.V. (2023). “Cellebrite UFED” hardware and software complex as a means of obtaining information from mobile terminals. In Current issues and prospects for the use of investigative tools in solving crimes under martial law: Material interdepartmental science and practice conferences (pp. 70-73). Kyiv: National Academy of Internal Affairs.
[12] Leonov, A. (2020). Intrusion into privacy. Retrieved from https://zib.com.ua/ua/142223.html.
[13] Manjre, B.M., Goyal, K.K., & Shivani. (2023). A novel and custom blockchain approach for the integrity assurance of the digital evidences extracted during the extraction and decoding of mobile artifacts from the mobile forensic tools. Advances in Material Science and Manufacturing Engineering, 2753(1), article number 030006. doi: 10.1063/5.0127910.
[14] Nassif, L.N. (2019). Conspiracy communication reconstitution from distributed instant messages timeline. In Institute for Electrical and Electronics Engineers (IEEE) wireless communications and networking conference workshop (pp. 1-6). New York: Institute for Electrical and Electronics Engineers. doi: 10.1109/ WCNCW.2019.8902574.
[15] Perumal, S., Navarathnam, S., De Vosse, C., Samsuddin, S.B., & Samy, G.N. (2017). Comparative studies on mobile forensic evidence extraction open source software for android phone. Advanced Science Letters, 23(5), 4483-4486. doi: 10.1166/asl.2017.8922.
[16] Pyrih, I.V. (2019). Involvement of specialists in investigative activities in the investigation of criminal offenses. In Realities and prospects for the development of the rule-of-law state in Ukraine and worldwide (pp. 93-122). Lviv: Liha-Pres. doi: 10.36059/978-966-397-207-7/93-122.
[17] Riadi, I., Yudhana, A., & Inngam Fanani, G.P. (2023). Mobile forensic tools for digital crime investigation: Comparison and evaluation. International Journal of Safety and Security Engineering, 13(1), 11-19. doi: 10.18280/ijsse.130102.
[18] Saleem, S., Popov, O., & Baggili, I. (2016). A method and a case study for the selection of the best available tool for mobile device forensics using decision analysis. Digital Investigation, 16, S55-S64. doi: 10.1016/j.diin.2016.01.008.
[19] Satpathy, S., & Mohanty, S. (Eds.). (2020). Big Data Analytics and computing for digital forensic investigations. Boca Raton: Chemical Rubber Company Press. doi: 10.1201/9781003024743.
[20] Sengupta, A., Singh, A., & Vinjit, B.M. (2023). A platform independent and forensically sound method to extract WhatsApp data from mobile phones. International Journal of Electronic Security and Digital Forensics, 15(3), 259-280. doi: 10.1504/IJESDF.2023.130657.
[21] Tara, H., & Mishra, A. (2021). A comparative study of digital forensic tools for data extraction from electronic devices. Journal of Punjab Academy of Forensic Medicine and Toxicology, 21(1), 97-104. doi: 10.5958/0974-083X.2021.00016.9.
[22] Teplytskyi, B.B. (2020). Application of criminal tools during a search during investigation of crimes in the field of use of computers, systems and computer networks and telecommunications networks. Legal Science, 5(107), 151-157. doi: 10.32844/2222-5374-2020-107-5-2.19.
[23] Wang, P., Rosenberg, M., & D’Cruze, H. (2018). Integration of mobile forensic tool capabilities. In S. Latifi (Ed.), Information technology – New generations. Advances in intelligent systems and computing (pp. 81-87). Cham: Springer. doi: 10.1007/978-3-319-77028-4_13.
[24] Williams, J., MacDermott, A., Stamp, K., & Iqbal, F. (2021). Forensic analysis of Fitbit versa: Android vs iOS. In 2021 Institute for Electrical and Electronics Engineers (IEEE) symposium on security and privacy workshops (pp. 318-326). San Francisco: Institute for Electrical and Electronics Engineers. doi: 10.1109/ SPW53761.2021.00052.