CRJul 7, 2015

Cyber-Deception and Attribution in Capture-the-Flag Exercises

arXiv:1507.01922v119 citations
Originality Synthesis-oriented
AI Analysis

This addresses attribution challenges in cybersecurity, but is incremental as it applies existing methods to new data.

The study tackled the problem of attributing cyber-attack culprits by using DEFCON capture-the-flag exercise data with known ground truth, finding that deceptive activities cause most misclassifications and exploring heuristics to reduce this.

Attributing the culprit of a cyber-attack is widely considered one of the major technical and policy challenges of cyber-security. 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 work, we use various classification techniques to identify the culprit in a cyberattack and find that deceptive activities account for the majority of misclassified samples. We also explore several heuristics to alleviate some of the misclassification caused by deception.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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