AI for Software Security

Dilli Prasad Sharma (), Arash Habibi Lashkari (), Mahdi Daghmehchi Firoozjaei (), Samaneh Mahdavifar () and Pulei Xiong ()
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Dilli Prasad Sharma: University of Toronto
Arash Habibi Lashkari: York University
Mahdi Daghmehchi Firoozjaei: MacEwan University
Samaneh Mahdavifar: McGill University
Pulei Xiong: National Research Council of Canada

Chapter Chapter 5 in Understanding AI in Cybersecurity and Secure AI, 2025, pp 69-93 from Springer

Abstract: Abstract Artificial Intelligence (AI) and Machine Learning (ML) are crucial in securing mobile, web, and desktop applications. This chapter presents an in-depth analysis of these advancements, offering insights into the future of AI-driven cybersecurity solutions for modern software applications by exploring key cybersecurity threats, including injection attacks, cross-site scripting (XSS), and insecure authentication. It highlights how AI-powered solutions enhance security through intelligent threat detection, automated vulnerability assessment, and adaptive patch management. We also discuss their integration into security tools like antivirus software, IDS/IPS, and firewalls.

Date: 2025
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DOI: 10.1007/978-3-031-91524-6_5

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