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).

Keywords

• Microsoft 365
• digital forensics analysis
• adversarial behavior patterns
• cybersecurity
• malicious login attempts
• data breaches