Generative AI for Software and Systems Security and Privacy

Dear Colleagues,

Software systems have become increasingly complex and critical to our daily lives. From cyber-physical systems to machine learning-based applications, these systems often involve intricate interactions between numerous components. Ensuring the reliability, security, and quality of these systems is paramount to preventing disruptions and potential harm.

Traditional approaches to software reliability, security, and quality assurance have focused on techniques like formal engineering, software testing, verification, and validation. While these methods have been valuable, the increasing complexity of modern software systems demands innovative solutions. Generative AI offers a promising avenue for addressing these challenges.

By leveraging the power of generative AI, we can develop more effective techniques for:

• Automated vulnerability detection: identifying security weaknesses in software systems that may be difficult to detect using traditional methods.
• Intelligent code generation: generating secure and reliable code snippets to enhance software quality and reduce the risk of errors.
• Privacy-preserving data analysis: analyzing data while protecting sensitive information, ensuring compliance with privacy regulations.
• Adaptive security systems: creating security systems that can learn and adapt to evolving threats, providing more robust protection.

This Special Issue invites high-quality research contributions that explore the application of generative AI to enhance software and systems security and privacy. We welcome submissions that address topics such as:

• Novel generative AI techniques for software vulnerability detection.
• Applications of generative AI for secure and reliable code generation.
• Privacy-preserving data analysis using generative AI.
• Adaptive security systems based on generative AI.
• Empirical/case studies demonstrating the effectiveness of generative AI in improving software security and privacy.

We believe that by fostering research and collaboration in this area, we can significantly advance the state of the art in software and systems security and privacy.

Dr. Haipeng Cai
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Software is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• novel generative AI techniques for software vulnerability detection
• applications of generative AI for secure and reliable code generation
• privacy-preserving data analysis using generative AI
• adaptive security systems based on generative AI
• empirical/case studies demonstrating the effectiveness of generative AI in improving software security and privacy