Predicting Security-Vulnerable Developers Based on Their Techno-Behavioral Characteristics

M. D. J. S. Goonetillake, Rangana Jayashanka and S. V. Rathnayaka
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M. D. J. S. Goonetillake: School of Computing, University of Colombo, Sri Lanka
Rangana Jayashanka: School of Computing, University of Colombo, Sri Lanka
S. V. Rathnayaka: School of Computing, University of Colombo, Sri Lanka

International Journal of Information Security and Privacy (IJISP), 2022, vol. 16, issue 1, 1-26

Abstract: Assigning developers for highly secured software projects requires identifying developers’ tendency to contribute towards vulnerable software codes called developer-centric security vulnerability to mitigate issues on human resource management, financial and project timelines. There are problems in assessing the previous codebases in evaluating the developer-centric security vulnerability level of each developer. Thus, this paper suggests a method to evaluate this through the techno-behavioral features of their previous projects. Consequently, we present results of an exploratory study of the developer-centric security vulnerability level prediction using a dataset of 1827 developers by logically selecting 13 techno-behavioral features. Our results depict that there is a correlation between techno-behavioral features and developer-centric security vulnerability with 89.46% accuracy. This model enables to predict developer-centric security vulnerability level of any developer if the required techno-behavioral features are available avoiding the analysis of his/her previous codebases.

Date: 2022
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