Source Code Author Identification Based on N-gram Author Profiles
- Cite this paper as:
- Frantzeskou G., Stamatatos E., Gritzalis S., Katsikas S. (2006) Source Code Author Identification Based on N-gram Author Profiles. In: Maglogiannis I., Karpouzis K., Bramer M. (eds) Artificial Intelligence Applications and Innovations. AIAI 2006. IFIP International Federation for Information Processing, vol 204. Springer, Boston, MA
Source code author identification deals with the task of identifying the most likely author of a computer program, given a set of predefined author candidates. This is usually. based on the analysis of other program samples of undisputed authorship by the same programmer. There are several cases where the application of such a method could be of a major benefit, such as authorship disputes, proof of authorship in court, tracing the source of code left in the system after a cyber attack, etc. We present a new approach, called the SCAP (Source Code Author Profiles) approach, based on byte-level n-gram profiles in order to represent a source code author’s style. Experiments on data sets of different programming language (Java or C++) and varying difficulty (6 to 30 candidate authors) demonstrate the effectiveness of the proposed approach. A comparison with a previous source code authorship identification study based on more complicated information shows that the SCAP approach is language independent and that n-gram author profiles are better able to capture the idiosyncrasies of the source code authors. Moreover the SCAP approach is able to deal surprisingly well with cases where only a limited amount of very short programs per programmer is available for training. It is also demonstrated that the effectiveness of the proposed model is not affected by the absence of comments in the source code, a condition usually met in cyber-crime cases.