Privacy Algorithms in Systems (PAS) Workshop

About

The goal of Privacy Algorithms in Systems workshop is to establish a platform where researchers and engineers can come together to address the challenges and propose solutions pertaining to privacy issues arising in systems for data-driven applications, with a particular focus on machine learning and data analytics. The impact of privacy extends across a wide range of systems spanning from databases, home management systems, user tracking devices, biomedical and communication systems, social networks, surveillance systems, smart grids, etc. These raise privacy concerns for private citizens, big corporations, and national infrastructure, as they often contain sensitive information that can be exploited, without the knowledge or consent of the involved party for various purposes (e.g., monitoring, discrimination, and illegal activities). This leads to efforts to develop effective privacy preservation algorithms and their integration into existing systems or built by design in the new systems for machine learning and data analytic. Therefore, we propose the PAS at AAAI’24, which provides a venue to gather experts to discuss the technical challenges of designing and integrating privacy-preservation algorithms into real-world systems.

Topics of Interest

We invite submissions that focus on recent advances in research, development of privacy algorithms, tools, libraries, and their applications. Papers are welcome from any of the following research areas, including but not limited to:

Implementation of privacy policies and regulations in privacy algorithms
Benchmark analysis and privacy attacks on data-driven systems for ML and data analytics
Privacy definitions for systems involving complex data (e.g., image, text, video, audio, streaming data, graph data)
Private data sharing for ML applications
Privacy preservation in ML models
Private data integration and cleaning for ML applications
Private federated learning

Also, for the following but not limited application areas::

Cyber-Physical systems, Transportation, Smart Grid, Medical equipment and others.

Submission Details

We invite three categories of papers before references and the review process is double-blind so the papers should be submitted anonymized. All submissions must be in PDF format and formatted according to the AAAI format published in AAAI 2024 LaTeX style file and following AAAI guidance and code of conduct. Submitted works will be assessed based on their novelty, technical quality, potential impact, and clarity of writing (and should be in English). For papers that primarily rely on empirical evaluations, the experimental settings and results should be clearly presented and repeatable. We encourage authors to make data and code available publicly when possible. We expect each paper will be reviewed by at least three reviewers.

Submissions can fall in one of the following categories: