Unmasking Cyber Adversaries: LeveragingCyber Threat Intelligence for AttackerBehavior Analysis

Security professionals need to advance their study of attacker behavior due to cyber security threatsbecoming increasingly complex. CTI works as an essential component by both identifying andassessing cyber threats through thorough TTP evaluation of adversaries to establish strategiccountermeasures. This document surveys the potential benefits which emerge when cyber threatintelligence systems merge with attacker behavior evaluations to establish predictive cyber securitydefenses. Post-incident analysis using the MITRE ATT & amp; CK framework in conjunction withthe Kill Chain Analysis framework allows us to identify pervasive attack methods and escalatingsecurity threats from authentic cyber-attacks. This paper evaluates machine learning along withartificial intelligence technologies which automate cyber operations. The model uses threatintelligence processes that support predictive threat modeling. Behavioral profiling constitutes afundamental tool for attributing threats and responding to incidents yet calls for perpetualinformation exchange between organizations according to investigation findings. The researchdevelops a CTI-driven defense model that stands as a proposed approach to increase defensesagainst sophisticated threat actors.