CRJan 10, 2017

On the Feasibility of Malware Authorship Attribution

arXiv:1701.02711v149 citations
Originality Synthesis-oriented
AI Analysis

This addresses the challenge of malware forensics for security analysts, but it is incremental as it builds on prior work without introducing a new method.

This paper tackles the problem of attributing malware authorship from binaries, where source code is unavailable, by analyzing features that survive compilation. It reviews existing techniques and identifies applicable features through a case study.

There are many occasions in which the security community is interested to discover the authorship of malware binaries, either for digital forensics analysis of malware corpora or for thwarting live threats of malware invasion. Such a discovery of authorship might be possible due to stylistic features inherent to software codes written by human programmers. Existing studies of authorship attribution of general purpose software mainly focus on source code, which is typically based on the style of programs and environment. However, those features critically depend on the availability of the program source code, which is usually not the case when dealing with malware binaries. Such program binaries often do not retain many semantic or stylistic features due to the compilation process. Therefore, authorship attribution in the domain of malware binaries based on features and styles that will survive the compilation process is challenging. This paper provides the state of the art in this literature. Further, we analyze the features involved in those techniques. By using a case study, we identify features that can survive the compilation process. Finally, we analyze existing works on binary authorship attribution and study their applicability to real malware binaries.

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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