Fine-grained binary code authorship identification

Abstract

Binary code authorship identification is the task of determining the authors of a piece of binary code from a set of known authors. Modern software often contains code from multiple authors. However, existing techniques assume that each program binary is written by a single author. We present a new finer-grained technique to the tougher problem of determining the author of each basic block. Our evaluation shows that our new technique can discriminate the author of a basic block with 52% accuracy among 282 authors, as opposed to 0.4% accuracy by random guess, and it provides a practical solution for identifying multiple authors in software.