UA Miner: Deep Learning Systems for Expose Unprotected API Vulnerability in Source Code
Application Programming Interface (API) documentation only describes the functions of the corresponding API and does not indicate how to use it safely. So, there are many unprotected API vulnerabilities in programs. Mining unprotected API (UA) vulnerabilities is a significant issue related to system security. In this paper, a system named UA Miner was proposed that can be automatically mine the unprotected API vulnerabilities by a series of techniques based on Deep Learning. The problem in which APIs need to be protected was solved by analyzing the published vulnerability information. The challenge of how to protect API correctly was solved by Deep Learning. In order to improve the effect of Deep Learning, the methods normalization, reducing the dimension of tokens were adopted. Heuristic Method was designed to solve the problem of sample imbalance, and samples were constructed from actual programs. We use 56000 samples to train and test UA Miner. The experimental results show that UA Miner can effectively mine unprotected API vulnerabilities, and is superior to the existing methods in effectiveness and accuracy.
2020 12th International Conference on Advanced Computational Intelligence (ICACI)