Over the past few decades, researchers have put their effort and paid significant attention to
the authorship attribution field, as it plays an important role in software forensics analysis …

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 …

With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …

Pre-trained models of code have achieved success in many important software engineering
tasks. However, these powerful models are vulnerable to adversarial attacks that slightly …

The detection of software vulnerabilities (or vulnerabilities for short) is an important problem
that has yet to be tackled, as manifested by the many vulnerabilities reported on a daily …

Large language models for code (LLM4Code), which demonstrate strong performance (eg,
high accuracy) in processing source code, have significantly transformed software …

In recent years, the task of generating realistic short and long texts have made tremendous
advancements. In particular, several recently proposed neural network-based language …

In this paper, we present a novel attack against authorship attribution of source code. We
exploit that recent attribution methods rest on machine learning and thus can be deceived by …

Abstract Advanced Persistent Threats (APTs) are highly sophisticated cyberattacks that are
aimed at achieving strategic goals and are usually backed by a well-funded entity. In this …

Neural machine translation models are used to automatically generate a document from
given source code since this can be regarded as a machine translation task. Source code …