Research Article
Software Vulnerabilities Detection Using a Trace-Based Analysis Model
@INPROCEEDINGS{10.1007/978-3-031-34896-9_27, author={Gouayon Koala and Didier Bassole and Telesphore Tiendrebeogo and Oumarou Sie}, title={Software Vulnerabilities Detection Using a Trace-Based Analysis Model}, proceedings={Towards new e-Infrastructure and e-Services for Developing Countries. 14th EAI International Conference, AFRICOMM 2022, Zanzibar, Tanzania, December 5-7, 2022, Proceedings}, proceedings_a={AFRICOMM}, year={2023}, month={6}, keywords={Execution traces Vulnerabilities Tracing techniques Applications Attacks}, doi={10.1007/978-3-031-34896-9_27} }- Gouayon Koala
Didier Bassole
Telesphore Tiendrebeogo
Oumarou Sie
Year: 2023
Software Vulnerabilities Detection Using a Trace-Based Analysis Model
AFRICOMM
Springer
DOI: 10.1007/978-3-031-34896-9_27
Abstract
Over the years, digital technology has grown considerably. With this growth, the information systems’ security has increasingly become a major concern. In this paper, we propose an analysis model based on application execution traces. This model makes it possible to improve the detection of vulnerabilities in applications. Indeed, after an evaluation of each of the tracing techniques we derived this model which takes into account these techniques and combines them with machine learning techniques. In this way, the applications undergo several analyses. This reduces the effect of evasion techniques used by hackers to circumvent the proposed solutions. We focused on Android applications because of their increasing popularity with a variety of services and features offered, making them a favourite target for hackers. These hackers use every means to exploit the slightest flaw in the applications. Unfortunately, the solutions proposed remain insufficient and sometimes ineffective in the face of their determination.
