A data-driven approach to prioritize MITRE ATT&CK techniques for active directory adversary emulation.

一种基于数据驱动的方法,用于确定 MITRE ATT&CK 技术在活动目录攻击者模拟中的优先级

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作者:Abo-Alian Alshaimaa, Youssef Mahmoud, Badr Nagwa L
Advanced Persistent Threats (APTs) continue to evolve, employing sophisticated and evasive techniques that pose significant challenges to modern defense mechanisms, particularly in Active Directory (AD) environments. Adversary emulation serves as a proactive security strategy, enabling organizations to replicate real-world adversary behaviors to assess and enhance detection, response, and mitigation capabilities. However, existing frameworks often lack a structured approach to prioritizing techniques based on impact, feasibility, and security control gaps, leading to suboptimal resource allocation. This study proposes a Multi-Criteria Decision-Making (MCDM) approach that integrates Operational Threat Intelligence (OTI) and structured datasets from MITRE ATT&CK to systematically prioritize adversary techniques. The methodology evaluates techniques across three key dimensions: Active Directory Impact, Threat Score, and Security Control Gap, employing entropy-based weighting to ensure an objective and data-driven prioritization process. To validate the proposed framework, a real-world case study based on the APT3 threat group is presented, demonstrating the applicability and effectiveness of the prioritization strategy in aligning adversary emulation with real-world attack scenarios. By focusing on high-impact and difficult-to-detect techniques, this framework enhances the effectiveness of adversary emulation and strengthens security postures in AD environments.

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