Enhancing Microsoft 365 Security: Integrating Digital Forensics Analysis to Detect and Mitigate Adversarial Behavior Patterns

Abstract

This research article investigates the effectiveness of digital forensics analysis (DFA) techniques in identifying patterns and trends in malicious failed login attempts linked to public data breaches or compromised email addresses in Microsoft 365 (M365) environments. Pattern recognition techniques are employed to analyze security logs, revealing insights into negative behavior patterns. The findings contribute to the literature on digital forensics, opposing behavior patterns, and cloud-based cybersecurity. Practical implications include the development of targeted defense strategies and the prioritization of prevalent threats. Future research should expand the scope to other cloud services and platforms, capture evolving trends through more prolonged and extended analysis periods, and assess the effectiveness of specific mitigation strategies for identified tactics, techniques, and procedures (TTPs).

An Interdisciplinary Approach to Enhancing Cyber Threat Prediction Utilizing Forensic Cyberpsychology and Digital Forensics

“…For instance, predictive models can forecast potential cyberattacks, and understanding the behavioral triggers, drivers, and patterns of cybercriminal behavior could significantly refine these predictions [24]. Similarly, integrating cyberpsychological profiles into digital forensics investigations could enhance accuracy regarding attribution, that is, identifying potential cybercriminals (lone and organized) and understanding respective modus operandi [1,25,26].…”

“…This synthesis improves accuracy and enriches the understanding of the complex interplay between technological vulnerabilities and human behaviors. The practical application of this approach is evident in scenarios where combined technical and behavioral analyses have successfully preempted sophisticated cyberattacks, demonstrating its efficacy in real-world cybersecurity challenges [3,25].…”

“…Cyber Behavioral Analysis Metric (CBAM): A metric used in cyber behavioral analysis to quantify and evaluate specific behaviors or trends in cyber environments [25,26].…”

“…Digital forensics (DF): Collecting, analyzing, and preserving digital evidence from cyber incidents. It is a crucial component of digital investigations and plays a significant role in the CFBA model [7,25]. 9.…”

“…Enhancing cyber threat prediction accuracy: At its core, the research advances the precision and accuracy of predicting cyber threats, specifically from ASNs, in contemporary cybersecurity contexts. By effectively combining the technical data from digital forensics (DF) with the behavioral insights of the cybercriminal, the study introduces an approach to understanding and mitigating cyber threats [8,25].…”