What question did this study set out to answer?

The aim is to provide a comprehensive overview of methods used for cyber threat actor attribution and their evolution over time.

Cyber Threat Actor Attribution: A Systematic Review and Evolutionary Perspective

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Systematic review analyzes methods for cyber threat attribution, highlighting trends in AI and graph learning, suggesting future directions.

The aim is to provide a comprehensive overview of methods used for cyber threat actor attribution and their evolution over time.
Conducted a systematic review of existing literature on cyber threat attribution methods
Proposed a taxonomy categorizing methods into text analysis, malware analysis, graph-based, and LLM-driven approaches
Examined trends leading to the development of multi-modal and explainable AI techniques.
Outlined the historical progression from probabilistic models to advanced AI techniques
Identified graph learning and retrieval-augmented generation as emerging trends
Suggested key future research directions for enhancing accuracy in attribution systems.

Aykhan Huseynli (2026) studied this question.

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Systematic review analyzes methods for cyber threat attribution, highlighting trends in AI and graph learning, suggesting future directions.