In this paper, we explore the idea of using locality sensitive hashes as input features to a feed-forward neural network with the goal of detecting JavaScript malware through static analysis. An experiment is conducted using a dataset containing 1.5M …
Statistical prediction models can be an effective technique to identify vulnerable components in large software projects. Two aspects of vulnerability prediction models have a profound impact on their performance: 1) the features (i.e., the …
Finding security vulnerabilities in the source code as early as possible is becoming more and more essential. In this respect, vulnerability prediction models have the potential to help the security assurance activities by identifying code locations …
Building secure software is difficult, time-consuming, and expensive. Prediction models that identify vulnerability prone software components can be used to focus security efforts, thus helping to reduce the time and effort required to secure …
This paper presents an approach based on machine learning to predict which components of a software application contain security vulnerabilities. The approach is based on text mining the source code of the components. Namely, each component is …