Background

Recent years have seen a dramatic increase in applications of artificial intelligence, machine learning, and data mining to security and privacy problems. 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. 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 AISec workshop, now in its 11th year, 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 on any topic in the intersection of AI or machine learning with security, privacy, or related areas.
• Position and open problem papers discussing the relationship of AI or machine learning to security or privacy. 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.
• "Systematization of knowledge" papers, which should distill the AI or machine learning contributions of a previously published series of security papers.

Paper Topics

Topics of interest include, but are not limited to:

Adversarial learning and related topics

• Adversarial attacks on machine learning models and algorithms
• Detection of adversarial attacks against machine learning models and algorithms
• Increasing robustness of machine learning models and algorithms to adversarial attacks
• Security of deep learning systems;
• Online Learning
• Measurement and ground truth acquisition
• Adaptive side-channel attacks

Security applications of AI and ML

• Computer Forensics
• Spam detection
• User authentication
• Phishing detection and prevention
• Botnet detection
• Intrusion detection and response
• Anomalous behavior detection
• Malware identification
• Data anonymization/de-anonymization
• Security in social networks
• Big data analytics for security

Security-related AI problems

• Distributed inference and decision making for security
• Secure multiparty computation and cryptographic approaches
• Privacy-preserving data mining
• Differential privacy
• Design and analysis of CAPTCHAs
• AI approaches to trust and reputation
• Vulnerability testing through intelligent probing (e.g. fuzzing)
• Techniques and methods for generating training and test sets
• Learning in games

Paper 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. Committee members are not required to read the appendices, so the paper should be intelligible without them. Submissions must be anonymized.

Papers should be in LaTeX in the new ACM format. This format is required for the camera-ready version. Please follow the main CCS formatting instructions (except with page limits as described above). In particular, we recommend using the CCS 2017 template, which can be downloaded from https://github.com/acmccs/format. Accepted papers will be published by the ACM Digital Library and/or ACM Press.

All submissions must be in English.

Submissions can be made through EasyChair using the following link: https://easychair.org/conferences/?conf=aisec2018