A list of the REPHRAIN Centre publications can be found below – please check back for regular updates.
August 2021
Polynomial Representation Is Tricky: Maliciously Secure Private Set Intersections Revisited
Prepared by Aydin Abadi, Steven Murdoch, Thomas Zacharias
Abstract: Private Set Intersection protocols (PSIs) allow parties to compute the intersection of their private sets, such that nothing about the sets’ elements beyond the intersection is revealed. PSIs have a variety of applications, primarily in efficiently supporting data sharing in a privacy-preserving manner. At Eurocrypt 2019, Ghosh and Nilges proposed three efficient PSIs based on the polynomial representation of sets and proved their security against active adversaries. In this work, we show that these three PSIs are susceptible to several serious attacks. The attacks let an adversary (1) learn the correct intersection while making its victim believe that the intersection is empty, (2) learn a certain element of its victim’s set beyond the intersection, and (3) delete multiple elements of its victim’s input set. We explain why the proofs did not identify these attacks and propose a set of mitigations.
Paper available for download here.
March 2021
Towards Data Scientific Investigations: A Comprehensive Data Science Framework and Case Study for Investigating Organized Crime and Serving the Public Interest
Prepared by Erik van de Sandt, Arthur van Bunningen, Jarmo van Lenthe, John Fokker
Abstract: Big Data problems thwart the effectiveness of today’s organized crime investigations. A frequently proposed solution is the introduction of ‘smart’ data science technologies to process raw data into factual evidence. This transition to – what we call – data scientific investigations is nothing less than a paradigm shift for law enforcement agencies, and cannot be done alone. Yet a common language for data scientific investigations is so far missing. This white paper therefore presents guiding principles and best practices for data scientific investigations of organized crime, developed and put into practice by operational experts over several years, while connecting to existing law enforcement and industry standards. The associated framework is called CSAE (pronounced as ‘see-say’): a comprehensive framework that consists of a business process, methodology, policy agenda and public interest philosophy for data scientific operations.
Paper available for download here.