A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response

In the dynamic landscape of digital forensics, the integration of Artificial Intelligence (AI) and Machine Learning (ML) stands as a transformative technology, poised to amplify the efficiency and precision of digital forensics investigations. However, the use of ML and AI in digital forensics is still in its nascent stages. As a result, this paper gives a thorough and in-depth analysis that goes beyond a simple survey and review. The goal is to look closely at how AI and ML techniques are used in digital forensics and incident response. This research explores cutting-edge research initiatives that cross domains such as data collection and recovery, the intricate reconstruction of cybercrime timelines, robust big data analysis, pattern recognition, safeguarding the chain of custody, and orchestrating responsive strategies to hacking incidents. This endeavour digs far beneath the surface to unearth the intricate ways AI-driven methodologies are shaping these crucial facets of digital forensics practice. While the promise of AI in digital forensics is evident, the challenges arising from increasing database sizes and evolving criminal tactics necessitate ongoing collaborative research and refinement within the digital forensics profession. This study examines the contributions, limitations, and gaps in the existing research, shedding light on the potential and limitations of AI and ML techniques. By exploring these different research areas, we highlight the critical need for strategic planning, continual research, and development to unlock AI's full potential in digital forensics and incident response. Ultimately, this paper underscores the significance of AI and ML integration in digital forensics, offering insights into their benefits, drawbacks, and broader implications for tackling modern cyber threats

Detection of Metasploit Attacks Using RAM Forensic on Proprietary Operating Systems

Information technology has become an essential thing in the digital era as it is today. With the support of computer networks, information technology is used as a medium for exchanging data and information. Much information is confidential. Therefore, security is also essential. Metasploit is one of the frameworks commonly used by penetration testers to audit or test the security of a computer system legally, but it does not rule out the possibility that Metasploit can also be used for crime. For this reason, it is necessary to carry out a digital forensic process to uncover these crimes. In this study, a simulation of attacks on Windows 10 will be carried out with Metasploit. Then the digital forensics process uses live forensics techniques on computer RAM, where the computer RAM contains information about the processes running on the computer. The live forensic technique is important because information on RAM will be lost if the computer is off. This research will use FTK Imager, Dumpit, and Magnet RAM Capture as the RAM acquisition tool and Volatility as the analysis tool. The results of the research have successfully shown that the live forensics technique in RAM is able to obtain digital evidence in the form of an attacker's IP, evidence of exploits/Trojans, processes running on RAM, operating system profiles used and the location of the exploits/Trojan when executed by the victim

Pro-active Meeting Assistants : Attention Please!

This paper gives an overview of pro-active meeting assistants, what they are and when they can be useful. We explain how to develop such assistants with respect to requirement definitions and elaborate on a set of Wizard of Oz experiments, aiming to find out in which form a meeting assistant should operate to be accepted by participants and whether the meeting effectiveness and efficiency can be improved by an assistant at all