This workshop surveyed emerging challenges in engineering privacy from applications of cryptographic protocols and privacy-preserving databases, to formal notations and programming languages in identity management, de-identification, and software specification. This survey reviewed known challenges, such as understanding privacy policies (e.g., privacy laws in regulated sectors like healthcare and finance; privacy promises in self-regulated sectors like Web services) in computational terms so that tools can be developed to help with their enforcement, which includes conflicts introduced by cross-references from one legal text to another, difficulties reflecting use based models, modeling business process’ compliance with the law; and policy weaknesses exposed by computer scientists that limit the utility of translation for privacy protection (e.g., the atomic view of information types that ignores statistical correlations leading to weak de-identification requirements and ineffective approaches to privacy-preserving big data analytics).

This was part of a series of workshops - view the series page.