JavaNeighbors: Improving ChuckyJava’s neighborhood discovery algorithm

In this paper, a study to protect Java Card source codes against fuzzing attacks is presented. This work is based on the tool ChuckyJava. This tool aims at automatically detecting anomalies in Java source codes in a Machine Learning way, without the knowledge of their specification. First, we propose a definition of neighbor methods. Based on this same definition, this study focuses on the improvement of the neighborhood discovery step for the tool ChuckyJava. To achieve this task, we have created a new Machine Learning tool: JavaNeighbors. It is based on different Natural Language Processing techniques: both local and global weighting schemes adjustement for term extraction and Latent Semantic Analysis to mitigate the curse of dimensionality. As a result, JavaNeighbors solves four limitations of ChuckyJava and it performs faster and with a better accuracy.