Code Authorship Attribution

Author:

Kalgutkar Vaibhavi1,Kaur Ratinder1ORCID,Gonzalez Hugo1,Stakhanova Natalia1,Matyukhina Alina1

Affiliation:

1. University of New Brunswick, NB, Canada

Abstract

Code authorship attribution is the process of identifying the author of a given code. With increasing numbers of malware and advanced mutation techniques, the authors of malware are creating a large number of malware variants. To better deal with this problem, methods for examining the authorship of malicious code are necessary. Code authorship attribution techniques can thus be utilized to identify and categorize the authors of malware. This information can help predict the types of tools and techniques that the author of a specific malware uses, as well as the manner in which the malware spreads and evolves. In this article, we present the first comprehensive review of research on code authorship attribution. The article summarizes various methods of authorship attribution and highlights challenges in the field.

Funder

New Brunswick Innovation Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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1. SepBIN: Binary Feature Separation for Better Semantic Comparison and Authorship Verification;IEEE Transactions on Information Forensics and Security;2024

2. Learning Explainable Multi-view Representations for Malware Authorship Attribution;2023 IEEE International Conference on Big Data (BigData);2023-12-15

3. Function-Level Code Obfuscation Detection Through Self-Attention-Guided Multi-Representation Fusion;International Journal of Software Engineering and Knowledge Engineering;2023-12-11

4. Discriminating Human-authored from ChatGPT-Generated Code Via Discernable Feature Analysis;2023 IEEE 34th International Symposium on Software Reliability Engineering Workshops (ISSREW);2023-10-09

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