Committee members are not required to read the appendices, so the paper should be intelligible without them. Accepted papers will be published by the ACM Digital Library and/or ACM Press. In particular, we recommend using the sigconf template, which can be downloaded from. Please follow the main CCS formatting instructions (except with page limits as described above).
This format is required for the camera-ready version. Papers should be in LaTeX and we recommend using the ACM format. Paper submissions must be at most 10 pages in double-column ACM format, excluding the bibliography and well-marked appendices, and at most 12 pages overall. The authors can specify the paper type in the submission form.
Stefano traverso series#
Systematization-of-knowledge papers, which should distill the AI or machine learning contributions of a previously-published series of security papers.Submitted papers of this type may not substantially overlap with papers that have been published previously or that are simultaneously submitted to a journal or conference/workshop proceedings. Position and open-problem papers discussing the relationship of AI or machine learning to security or privacy.Original research papers on any topic in the intersection of AI or machine learning with security, privacy, or related areas.Techniques and methods for generating training and test sets.Content-driven security policy management & access control.Vulnerability testing through intelligent probing (e.g.Secure multiparty computation and cryptographic approaches.Distributed inference and decision making for security.Topics of interest include (but are not limited to): The AISec workshop, now in its 15th year, is the leading venue for presenting and discussing new developments in the intersection of security and privacy with AI and machine learning. The recent widespread adoption of deep learning techniques, whose security properties are difficult to reason about directly, has only added to the importance of this research. The use of AI and ML in security-sensitive domains, in which adversaries may attempt to mislead or evade intelligent machines, creates new frontiers for security research. Recent years have seen a dramatic increase in applications of artificial intelligence, machine learning, and data mining to security and privacy problems. Camera ready due: September 05 September 16, 2022.Acceptance notification: August 05 September 02, 2022.Author response due: August 01 August 26, 2022.Reviews released: July 25 August 23, 2022.
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