Homomorphic Encryption for Speaker Recognition: Protection of Biometric Templates and Vendor Model Parameters

Data privacy is crucial when dealing with biometric data. Accounting for the latest European data privacy regulation and payment service directive, biometric template protection is essential for any commercial application. Ensuring unlinkability across biometric service operators, irreversibility of leaked encrypted templates, and renewability of e.g., voice models following the i-vector paradigm, biometric voice-based systems are prepared for the latest EU data privacy legislation. Employing Paillier cryptosystems, Euclidean and cosine comparators are known to ensure data privacy demands, without loss of discrimination nor calibration performance. Bridging gaps from template protection to speaker recognition, two architectures are proposed for the two-covariance comparator, serving as a generative model in this study. The first architecture preserves privacy of biometric data capture subjects. In the second architecture, model parameters of the comparator are encrypted as well, such that biometric service providers can supply the same comparison modules employing different key pairs to multiple biometric service operators. An experimental proof-of-concept and complexity analysis is carried out on the data from the 2013-2014 NIST i-vector machine learning challenge

Big Data Privacy Context: Literature Effects On Secure Informational Assets

This article's objective is the identification of research opportunities in the current big data privacy domain, evaluating literature effects on secure informational assets. Until now, no study has analyzed such relation. Its results can foster science, technologies and businesses. To achieve these objectives, a big data privacy Systematic Literature Review (SLR) is performed on the main scientific peer reviewed journals in Scopus database. Bibliometrics and text mining analysis complement the SLR. This study provides support to big data privacy researchers on: most and least researched themes, research novelty, most cited works and authors, themes evolution through time and many others. In addition, TOPSIS and VIKOR ranks were developed to evaluate literature effects versus informational assets indicators. Secure Internet Servers (SIS) was chosen as decision criteria. Results show that big data privacy literature is strongly focused on computational aspects. However, individuals, societies, organizations and governments face a technological change that has just started to be investigated, with growing concerns on law and regulation aspects. TOPSIS and VIKOR Ranks differed in several positions and the only consistent country between literature and SIS adoption is the United States. Countries in the lowest ranking positions represent future research opportunities.Comment: 21 pages, 9 figure

Data privacy by design: digital infrastructures for clinical collaborations

The clinical sciences have arguably the most stringent security demands on the adoption and roll-out of collaborative e-Infrastructure solutions such as those based upon Grid-based middleware. Experiences from the Medical Research Council (MRC) funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project and numerous other real world security driven projects at the UK e-Science National e-Science Centre (NeSC – www.nesc.ac.uk) have shown that whilst advanced Grid security and middleware solutions now offer capabilities to address many of the distributed data and security challenges in the clinical domain, the real clinical world as typified by organizations such as the National Health Service (NHS) in the UK are extremely wary of adoption of such technologies: firewalls; ethics; information governance, software validation, and the actual realities of existing infrastructures need to be considered from the outset. Based on these experiences we present a novel data linkage and anonymisation infrastructure that has been developed with close co-operation of the various stakeholders in the clinical domain (including the NHS) that addresses their concerns and satisfies the needs of the academic clinical research community. We demonstrate the implementation of this infrastructure through a representative clinical study on chronic diseases in Scotland

Microsoft and the European Union Face Off Over Internet Privacy Concerns

Amidst what appears to be a multi-faceted attack by the European Union on Microsoft, the newest angle is the European Commission\u27s announcement last month that it was considering a formal investigation of Microsoft\u27s .Net Passport data processing system for possible violations of the European Union Data Privacy Directive. This iBrief explores the European Data Privacy Directive and seeks to explain why the European Commission believes .Net Passport may be in violation of its privacy policies and a case for further investigation

iPDA: An Integrity-Protecting Private Data Aggregation Scheme for Wireless Sensor Networks

Data aggregation is an efficient mechanism widely used in wireless sensor networks (WSN) to collect statistics about data of interests. However, the shared-medium nature of communication makes the WSNs are vulnerable to eavesdropping and packet tampering/injection by adversaries. Hence, how to protect data privacy and data integrity are two major challenges for data aggregation in wireless sensor networks. In this paper, we present iPDA??????an integrity-protecting private data aggregation scheme. In iPDA, data privacy is achieved through data slicing and assembling technique; and data integrity is achieved through redundancy by constructing disjoint aggregation paths/trees to collect data of interests. In iPDA, the data integrity-protection and data privacy-preservation mechanisms work synergistically. We evaluate the iPDA scheme in terms of the efficacy of privacy preservation, communication overhead, and data aggregation accuracy, comparing with a typical data aggregation scheme--- TAG, where no integrity protection and privacy preservation is provided. Both theoretical analysis and simulation results show that iPDA achieves the design goals while still maintains the efficiency of data aggregation