Security, Privacy and Information Theory

Scope and topics of interest

Protect-IT focuses on the security and privacy of machine learning (ML) from an information-theoretic standpoint. ML systems rely on extensive datasets, often containing sensitive personal information, posing a threat to user privacy and security. Protect-IT aims to bring together experts in machine learning, (algorithmic) fairness and information theory to explore, develop, and evaluate privacy, security, and fairness attacks against ML algorithms along with defense strategies to counter them.

• Information leakage, data correlation
• Defining and quantifying privacy
• Differential privacy and private data analysis
• Machine learning and privacy
• Transparency, robustness, and abuse in privacy systems
• Information theoretic foundations of security and privacy
• Cryptographic tools for privacy
• Algorithmic fairness
• Adversarial learning
• Intrusion detection
• Privacy and security attacks and defenses

Call For Papers & Important Dates

Download Full CFP

Submission deadline: February 21, 2025, 23:59 (Anywhere on Earth)
Notification of acceptance: April 08, 2025

Submission Instructions

We welcome two types of submissions: full papers of maximum 12 pages or extended abstracts up to 4 pages. Full papers must be unpublished elsewhere and will be published in ACM digital library as workshop proceedings. We encourage submissions of work that is new to the community of data privacy, security and information theory. Extended abstracts can be previously published or currently under review elsewhere and will not be included in proceedings. All submissions must adhere the latest ACM Sigconf style conference template. We also welcome recently published studies as well as unpublished recent results in privacy and security venues only as poster submissions.

Poster Instructions

In addition to the accepted poster submissions of recent results, all accepted full paper submissions will have a slot at the poster session for posters with size no bigger than A0 (841 × 1189 mm).

Invited Speakers

• Castuscia Palamidessi - INRIA, LIX

Organization

Workshop chairs

• Ayşe Ünsal - EURECOM
• Javier Parra Arnau - Universitat Politècnica de Catalunya
• Natasha Fernandes - Macquarie University, Australia

Publications chair

• Natasha Fernandes - Macquarie University, Australia

Program Committee

• Aurélien Bellet - INRIA
• Josep Domingo-Ferrer - University of Rovira i Virgili
• Emre Gürsoy - Koç University
• Weizhi Meng - Technical University of Denmark
• Tobias Oechtering - Royal Institute of Technology
• Parastoo Sadeghi - University of New South Wales
• Thorsten Strufe - Karlsruhe Institute of Technology
• Vicenç Torra - Umeå University

Sponsors

Previous Editions

• Protect-IT'24 @ CSF