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Published in:
2015 | OriginalPaper | Chapter
Automated Classification of C&C Connections Through Malware URL Clustering
Authors : Nizar Kheir, Gregory Blanc, Hervé Debar, Joaquin Garcia-Alfaro, Dingqi Yang
Published in: ICT Systems Security and Privacy Protection
Publisher: Springer International Publishing
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We present WebVisor, an automated tool to derive patterns from malware Command and Control (C&C) server connections. From collective network communications stored on a large-scale malware dataset, WebVisor establishes the underlying patterns among samples of the same malware families (e.g., families in terms of development tools). WebVisor focuses on C&C channels based on the Hypertext Transfer Protocol (HTTP). First, it builds clusters based on the statistical features of the HTTP-based Uniform Resource Locators (URLs) stored in the malware dataset. Then, it conducts a fine-grained, noise-agnostic clustering process, based on the structure and semantic features of the URLs. We present experimental results using a software prototype of WebVisor and real-world malware datasets.