A method of vulnerability analysis based on deep learning for open source software

Abstract The vulnerability is defined as the weakness in the software system in terms of safety. In detail, the vulnerability is arisen from software failure resulted from the computer software of operating system. Many open source software are embedded in the commercial software. Then, the open source software is successful in achieving the cost reduction for several companies. Almost all of the open source software are developed by using the bug tracking system. Then, several nonfixed faults are embedded in the open source software. In particular, these nonfixed faults damage the system as critical faults. A lot of software reliability growth models have been proposed in order to assess software reliability and safety. However, there is no method for vulnerability assessment based on the fault big data for open source software. In this chapter, we discuss the method of vulnerability assessment based on the deep learning in order to consider the security of OSS project. Moreover, several numerical illustrations based on actual fault big data are shown by using the method of vulnerability assessment proposed in this chapter. Finally, we show that the proposed method is helpful to assess the vulnerability of open source software.