Abstract
Security of software is still today a critical requirement as a lot of attacks exploit vulnerabilities in code. Securing software is, however, a complex process that requires, among other activities, analyzing the software specification and implementation. Many ML-based techniques or ML-based enhancements of conventional techniques have thus been proposed. In this chapter, we cover ML techniques for static analysis and ML-based fuzzing. We also discuss natural language processing techniques for the analysis of software specifications written in natural language to support different security-related tasks.
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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
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Bertino, E. et al. (2023). Software Security Analysis. In: Machine Learning Techniques for Cybersecurity. Synthesis Lectures on Information Security, Privacy, and Trust. Springer, Cham. https://doi.org/10.1007/978-3-031-28259-1_4
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DOI: https://doi.org/10.1007/978-3-031-28259-1_4
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Publisher Name: Springer, Cham
Print ISBN: 978-3-031-28258-4
Online ISBN: 978-3-031-28259-1
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