Efficient usage of web forensics, disk forensics and email forensics in successful investigation of cyber crime

被引:1
作者
Pandey B. [1 ,4 ]
Pandey P. [2 ]
Kulmuratova A. [3 ]
Rzayeva L. [1 ]
机构
[1] Department of Intelligent System and Cyber Security, Astana IT University, Astana
[2] Gyancity Research Consultancy Pvt Ltd, Greater Noida
[3] Eurasian National University, Astana
[4] Faculty of Informatics and Computing, Universiti Sultan Zainul Abidin (UniSZA), Terengganu
关键词
Cyber forensic investigation; Cyber security; Disk forensics; Email forensics; Web foresnsics;
D O I
10.1007/s41870-024-02014-6
中图分类号
学科分类号
摘要
This paper is a fusion of a survey of different existing research related to web forensics, disk forensics, and email forensics and the implementation of the best practices in these areas. During the survey of ongoing state-of-the-art research, we observed that every forensic investigation process goes through five phases: identification of evidence, collection of evidence, examination of evidence, assessment/investigation of evidence, and reporting of evidence. Although phases are the same in all forensics investigations, for every forensics investigation there is a specialized set of forensics tools. This paper also highlights the need for intelligent tool selection and current challenges of web forensics, disk forensics, and email forensics and infers future research trends toward solving these current challenges. Eventually, we performed various case studies of web forensics, disk forensics, and email forensics and added three interesting investigations to this paper. The change in the price of items in the shopping cart on an e-commerce website before checkout is a case study of web forensics. To obtain system files using forensic tool kit (FTK) imager is a case study of disk forensics. Show original of g-mail is a case study of email forensics. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.
引用
收藏
页码:3815 / 3824
页数:9
相关论文
共 40 条
[1]  
Goel N., Ganotra D., An approach for anti-forensic contrast enhancement detection using grey level co-occurrence matrix and Zernike moments, Int J Inf Tecnol, 15, pp. 1625-1636, (2023)
[2]  
Surange G., Khatri P., Integrated intelligent IOT forensic framework for data acquisition through open-source tools, Int J Inf Tecnol, 14, pp. 3011-3018, (2022)
[3]  
Ramazhamba P.T., Venter H.S., Using distributed ledger technology for digital forensic investigation purposes on tendering projects, Int J Inf Tecnol, 15, pp. 1255-1274, (2023)
[4]  
Choudhary A.K., Rahamatkar S., Purbey S., DQNANFCT: design of a deep Q-learning network for augmented network forensics via integrated contextual trust operations, Int J Inf Tecnol, 15, pp. 2729-2739, (2023)
[5]  
Sharma P., Nagpal B., Regex: an experimental approach for searching in cyber forensics, Int J Inf Tecnol, 12, pp. 339-343, (2020)
[6]  
Patil R.Y., Patil Y.H., Bannore A., Et al., Ensuring accountability in digital forensics with proxy re-encryption based chain of custody, Int J Inf Tecnol, 16, pp. 1841-1853, (2024)
[7]  
Nelson R., Shukla A., Smith C., Web browser forensics in google chrome, mozilla firefox, and the tor browser bundle, Digital Forensic Education., 61, (2020)
[8]  
Javed A.R., Et al., A comprehensive survey on computer forensics: state-of-the-art, tools, techniques, challenges, and future directions, IEEE Access, 10, pp. 11065-11089, (2022)
[9]  
Chiramdasu R., Srivastava G., Bhattacharya S., Reddy P.K., Gadekallu T.R., Malicious URL detection using logistic regression, IEEE International Conference on Omni-Layer Intelligent Systems (COINS), pp. 1-6, (2021)
[10]  
Chen Y.-H., Chen J.-L., Ai@ntiphish—machine learning mechanisms for cyber-phishing attack, IEICE Trans Inf Syst, 102, 5, pp. 878-887, (2019)