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Despite the fact that cyberattacks are constantly growing in complexity, theresearch community still lacks effective tools to easily monitor and understandthem. In particular, there is a need for techniques that are able to not onlytrack how prominently certain malicious actions, such as the exploitation ofspecific vulnerabilities, are exploited in the wild, but also (and moreimportantly) how these malicious actions factor in as attack steps in morecomplex cyberattacks. In this paper we present ATTACK2VEC, a system that usestemporal word embeddings to model how attack steps are exploited in the wild,and track how they evolve. We test ATTACK2VEC on a dataset of billions ofsecurity events collected from the customers of a commercial IntrusionPrevention System over a period of two years, and show that our approach iseffective in monitoring the emergence of new attack strategies in the wild andin flagging which attack steps are often used together by attackers (e.g.,vulnerabilities that are frequently exploited together). ATTACK2VEC provides auseful tool for researchers and practitioners to better understand cyberattacksand their evolution, and use this knowledge to improve situational awarenessand develop proactive defenses.

ATTACK2VEC: Leveraging Temporal Word Embeddings to Understand the Evolution of Cyberattacks