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 …

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 …

Instead of only considering technology, computer security research now strives to also take
into account the human factor by studying regular users and, to a lesser extent, experts like …

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 …

Source code authorship attribution is an important problem often encountered in
applications such as software forensics, bug fixing, and software quality analysis. Recent …

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

Authorship attribution (ie, determining who is the author of a piece of source code) is an
established research topic. State-of-the-art results for the authorship attribution problem look …

Attributing a piece of malware to its creator typically requires threat intelligence. Binary
attribution increases the level of difficulty as it mostly relies upon the ability to disassemble …

Blockchain users are identified by addresses (public keys), which cannot be easily linked
back to them without out‐of‐network information. This provides pseudo‐anonymity, which is …

Authors writing documents imprint identifying information within their texts: vocabulary,
registry, punctuation, misspellings, or even emoji usage. Finding these details is very …