9th ACM Workshop on Artificial Intelligence and Security
with the 23nd ACM Conference on Computer and Communications (CCS)
October 28, 2016, Hofburg Palace, Vienna, Austria.


  • About

Call For Papers


Recent years have seen a dramatic increase in applications of artificial intelligence (AI), machine learning, and data mining to security and privacy problems. The analytic tools and intelligent behavior provided by these techniques make AI and learning increasingly important for autonomous real- time analysis and decision making in domains with a wealth of data or that require quick reactions to ever-changing situations. The use of learning methods in security-sensitive domains creates new frontiers for security research, in which adversaries may attempt to mislead or evade intelligent machines. Additionally, data mining and machine learning techniques create a wealth of privacy issues, due to the abudance and accessibility of data. The AISec workshop provides a venue for presenting and discussing new developments in the intersection of security and privacy with AI and machine learning.

Scope of Papers

We invite the following types of papers:

  • Original research papers describing the use of AI or machine learning in security, privacy and related areas.
  • Position and open problem papers discussing the role of AI or machine learning in security and privacy. Submitted papers of these types may not substantially overlap papers that have been published previously or that are simultaneously submitted to a journal or conference/workshop proceedings.
  • Systematization of knowledge papers, which should distill the AI or machine learning contributions of a previously published series of security papers.
  • Special topic: Papers describing advances in researching and deploying systems that combine machine learning and security at massive scale.
  • Presentation only papers for research currently under review elsewhere or published anytime after September 2014. These will not be published in the proceedings. They will undergo a light review for correctness, relevance and importance.

Paper format

This year we invite both original submissions and presentation-only papers. Please indicate the type of submission when submitting.

All submissions must be at most 10 pages in double-column ACM format (note: pages must be numbered), excluding the bibliography and well-marked appendices, and at most 12 pages overall. Committee members are not required to read the appendices, so the paper should be intelligible without them. Submissions must be anonymized. We recommend the use of the ACM SIG Proceedings templates for submissions. The ACM format is the required template for the camera-ready version. Accepted papers will be published by the ACM Digital Library and/or ACM Press. To meet page numbering requirements, you may use the following modified "style file" for initial submissions (thanks to Battista Biggio): modified ACM template. Submissions can be made through EasyChair using the following link: https://www.easychair.org/conferences/?conf=aisec2016

Topics of interest include, but are not limited to:

Theoretical topics related to security

  • Adversarial Learning
  • Robust Statistics
  • Online Learning
  • Learning in games
  • Economics of security
  • Differential privacy

Security applications

  • Computer Forensics
  • Spam detection
  • Phishing detection and prevention
  • Botnet detection
  • Intrusion detection and response
  • Malware identification
  • Authorship Identification

Security-related AI problems

  • Distributed inference and decision making for security
  • Secure multiparty computation and cryptographic approaches
  • Privacy-preserving data mining
  • Adaptive side-channel attacks
  • Design and analysis of CAPTCHAs
  • AI approaches to trust and reputation
  • Vulnerability testing through intelligent probing (e.g. fuzzing)
  • Content-driven security policy management & access control
  • Techniques and methods for generating training and test sets
  • Anomalous behavior detection (e.g. for the purposes of fraud prevention, authentication)

Special topic: Machine learning and security at massive scale

  • High-throughput abuse detection systems
  • Large-scale active learning
  • Big data analytics for security
  • Systems defending against multiple attack vectors
  • Techniques dealing with well-resourced adversaries