Eavesdropping Whilst You're Shopping: Balancing Personalisation and Privacy in Connected Retail Spaces

Physical retailers, who once led the way in tracking with loyalty cards and `reverse appends', now lag behind online competitors. Yet we might be seeing these tables turn, as many increasingly deploy technologies ranging from simple sensors to advanced emotion detection systems, even enabling them to tailor prices and shopping experiences on a per-customer basis. Here, we examine these in-store tracking technologies in the retail context, and evaluate them from both technical and regulatory standpoints. We first introduce the relevant technologies in context, before considering privacy impacts, the current remedies individuals might seek through technology and the law, and those remedies' limitations. To illustrate challenging tensions in this space we consider the feasibility of technical and legal approaches to both a) the recent `Go' store concept from Amazon which requires fine-grained, multi-modal tracking to function as a shop, and b) current challenges in opting in or out of increasingly pervasive passive Wi-Fi tracking. The `Go' store presents significant challenges with its legality in Europe significantly unclear and unilateral, technical measures to avoid biometric tracking likely ineffective. In the case of MAC addresses, we see a difficult-to-reconcile clash between privacy-as-confidentiality and privacy-as-control, and suggest a technical framework which might help balance the two. Significant challenges exist when seeking to balance personalisation with privacy, and researchers must work together, including across the boundaries of preferred privacy definitions, to come up with solutions that draw on both technology and the legal frameworks to provide effective and proportionate protection. Retailers, simultaneously, must ensure that their tracking is not just legal, but worthy of the trust of concerned data subjects.Comment: 10 pages, 1 figure, Proceedings of the PETRAS/IoTUK/IET Living in the Internet of Things Conference, London, United Kingdom, 28-29 March 201

Protected Facial Biometric Templates Based on Local Gabor Patterns and Adaptive Bloom Filters

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.M. Gómez-Barrero, C. Rathgeb, J. Galbally, J. Fiérrez, C. Busch, "Protected Facial Biometric Templates Based on Local Gabor Patterns and Adaptive Bloom Filters" in International Conference on Pattern Recognition (ICPR), Stockholm (Swede), 2014, 4483 - 4488Biometric data are considered sensitive personal data and any privacy leakage poses severe security risks. Biometric templates should hence be protected, obscuring the biometric signal in a non-reversible manner, while preserving the unprotected system's performance. In the present work, irreversible face templates based on adaptive Bloom filters are proposed. Experiments are carried out on the publicly available Bio Secure DB utilizing the free Bob image processing toolbox, so that research is fully reproducible. The performance and security evaluations proof the irreversibility of the protected templates, while preserving the verification performance. Furthermore, template size is considerably reduced.This work has been partially supported by projects Bio-Shield (TEC2012-34881) from Spanish MINECO, TABULARASA (FP7-ICT-257289), FIDELITY (FP7-SEC-284862) and BEAT (FP7-SEC-284989) from EU, the Center of Applied Security Research Darmstadt (CASED) and Cátedra UAM Telefónica