Abstract
Attributing the culprit of a cyberattack is widely considered one of the major technical and policy challenges of cybersecurity. While the lack of ground truth for an individual responsible for a given attack has limited previous studies, here we overcome this limitation by leveraging DEFCON capture-the-flag (CTF) exercise data where the actual ground truth is known. In this chapter, we use various classification techniques to identify the culprit in a cyberattack and find that deceptive activities account for the majority of misclassified attacks. We also explore several heuristics to alleviate some of the misclassification caused by deception.
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Nunes, E., Shakarian, P., Simari, G.I., Ruef, A. (2018). Baseline Cyber Attribution Models. In: Artificial Intelligence Tools for Cyber Attribution. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-73788-1_2
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DOI: https://doi.org/10.1007/978-3-319-73788-1_2
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