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Call For Papers: Special Issue on Autonomous AI Agents in Computer Security

IEEE Security & Privacy seeks submissions for this upcoming issue.

Submission deadline: 1 May 2026

Publication: Nov/Dec 2026


AI is having a transformative impact on cyber security that has the potential to significantly disrupt the effectiveness of current defensive standards. AI is up-scaling the offensive security tactics of novice and sophisticated attackers, at speed, scale, and potentially unseen methods targeting AI systems and supply chains. At the same time, autonomous AI agents offer the potential to counter these threats by enhancing the automatization of their detection, analysis, and recovery. However, the rapid pace of AI transformation and the resulting security arms race is creating significant uncertainty about what threats to expect and how to fortify defenses effectively.

This uncertainty is further amplified by the growing integration of autonomous agents across vertical and horizontal levels of global society, ranging from personal assistance to global commerce. Because of the potential capacity of these agents to interact with many parts of the economy, and to directly or indirectly touch critical systems, it will be essential to prioritize and integrate automated security at the outset as well. This necessitates a comprehensive analysis of both the vulnerabilities introduced through AI agents as well as their robustness and defensive capabilities.

As a result of these implications, we propose to explore the challenges, opportunities, and limitations arising from autonomous AI agents in computer security. The theme will focus on autonomous offensive and defensive security. The goal of the special issue is to uncover research directions to accelerate vulnerability discovery, attack detection, and incident response with automated, repeatable, and measurable approaches.

We’ll invite papers covering any aspect of AI agents for cyber security including, but not limited to,

  • AI agents for autonomous cyber defense
  • AI agents for autonomous vulnerability discovery and analysis
  • AI agents for autonomous incident recovery and response
  • Measurements quantifying the security of AI agents
  • Capabilities and limitations of AI agents in security contexts
  • Security analysis and vulnerability assessment of AI agents
  • Implications of AI agents for attack-defender asymmetries

Submission Instructions:

For author information and guidelines on submission criteria, please visit the Author Information page. As stated in the Author Information, peer-reviewed articles should run between 4,900 to 7,200 words, including all main body, abstract, keyword, bibliography, biography, and table text. The word count should include 250 words for each table and figure. There should be no more than 15 references. The abstract word limit is 50 words. Please submit full papers through the IEEE Author Portal system,  and be sure to select the special-issue or special-section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the IEEE Author Portal. All submitted manuscripts will undergo a single-anonymous peer review.

In addition to submitting your paper to IEEE Security & Privacy, you are also encouraged to upload the data related to your paper to IEEE DataPort. IEEE DataPort is IEEE's data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission. Thank you!


Questions?

For more information about the focus, contact the guest editors:

  • Álvaro A. Cárdenas,  University of California, Santa Cruz
  • Nicole Nichols, Palo Alto Networks
  • Kathrin Grosse, IBM research Zurich
  • Konrad Rieck,  Technische Universität Berlin & BIFOLD
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