Workshop: Theory and Science of Obfuscation as a Methodology for Privacy and Security

New York University, New York NY

Investigators

Abstract

Obfuscation studies how to insert noise into an existing signal to make data or information-stream more ambiguous, confusing, harder to exploit, and more difficult to act on. As an important topic in both privacy/security and information processing, it has been studied from many different perspectives in many related areas, e.g., data privacy, databases, machine learning, ethics, etc. This workshop represents one of the first attempts to consolidate and shape the area as a whole, and help develop a new research community that carries out obfuscation research in a holistic fashion. Specifically, this workshop aims to foster and develop new interdisciplinary research partnerships around obfuscation, by involving researchers, designers, and system producers, including but not limited to academic researchers, industry researchers and practitioners, and independent software producers and privacy activists. The workshop seeks to create benchmarks, assessment tools, and evaluation frameworks for obfuscation techniques, formalizing the notion of obfuscation, and identifying its key challenges and use cases. Through open, online publications, this workshop contributes to the broader conversation about putting obfuscation in practice, and therefore has broader impacts on industry and government, as well as user and developer communities who are interested in producing the next-generation privacy technologies.