Advancing Digital Forensics Education With Generative AI for Sustainable Development Goals

Author:

Hussain Naziya1ORCID,Dankan Gowda V.2ORCID,Swetha K. R.3,Junnarkar Aparna Atul4,Kawale Sheetalrani R.5ORCID

Affiliation:

1. School of Computers, IPS Academy, Indore, India

2. Department of Electronics and Communication Engineering, BMS Institute of Technology and Management, Bangalore, India

3. Department of Computer Science and Engineering, BGS Institute of Technology, Adichunchanagiri University, Mandya, India

4. Department of Information Technology, Vishwakarma Institute of Information Technology (VIIT), Pune, India

5. Department of Computer Science, Karnataka State Akkamahadevi Women University, Vijayapura, India

Abstract

The term “forensics” refers to a broad range of activities that involve gathering, analyzing, and presenting evidence that is admissible in a court of law and are intended to investigate potential entities. In particular, network and computer forensics examine a wide range of data in order to find evidence that can be used in court. During the forensic process, the examination and auditing of computer and network data is essential for gathering data, identifying breaches, and presenting legal evidence. In computer and network forensics, evidence relating to cybercrime is identified, acquired, extracted, examined, analyzed, interpreted, documented, and presented using a methodical, scientific approach. The field of network and computer forensics is constantly expanding, and as crimes move beyond computers and into networks, clouds, and social networks, it is essential to stay current with the newest tools and techniques. The goal of this chapter is to study and explore the methods and tools used in network and computer forensics.

Publisher

IGI Global

Reference22 articles.

1. Anaya, E. A., Nakano-Miyatake, M., & Perez Meana, H. M. (2019) Network forensics with Neurofuzzy techniques. In: 52nd IEEE international Midwest Symposium on Circuits and Systems (MWSCAS ’19). IEEE.

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3. Real-Time Applications of Machine Learning in Cyber-Physical Systems

4. Network Forensics: An Analysis of Techniques, Tools, and Trends

5. Jing, Y. N., Tu, P., Wang, X. P., & Zhang, G. D. (2015). Distributed-log-based scheme for IP traceback. The fifth international conference on Computer and Information Technology (CIT’ 15), Shanghai, China.

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