A private Intelligent Shopping Mall

In this paper we extend a previous recent work on Ambient Intelligence, deployed into a scenario of Intelligence Shopping Malls, with a privacy layer. In fact nowadays, in the Ambient Intelligence context, privacy issues are more and more considered an urgent and main issue to take care of. The success of this permeated ubiquitous intelligence seems to be strongly correlated to how much the scenario is able to protect the privacy and the rights of the users. The Intelligence Shopping Mall is a physical environment for commerce equipped with sensors and actuators for supporting shoppers. These latters have a wish list of the items to buy. Once in the mall, the wish list should be disclosed to steer the shopper towards the right shop selling the wished item. Anyway, from shops' point of view, shopping lists contain valuable information about shoppers. Indeed, from shopping lists one could easily infer users' personal preferences or tendency (e.g., users' lifestyle) that could be used for marketing purpose. Hence, shopping lists could reveal shoppers' sensitive information. In this paper, to preserve the shoppers' privacy without limiting the possibility to guide users towards shops selling the sought products, we propose an efficient and efficacious privacy preserving protocol. Using such a protocol, shops can steer shoppers towards the shops selling the desired items without knowing the items in their shopping lists (excluding the items bought in the shop itself).

[1]  Mimmo Parente,et al.  An Agent-Based Framework for Indoor Navigation in Blended Shopping , 2015, 2015 IEEE Symposium Series on Computational Intelligence.

[2]  He Jian,et al.  Modeling the Ambient Intelligence Application System: Concept, Software, Data, and Network , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[3]  Matteo Gaeta,et al.  A genetic approach to plan shopping in the AmI-based Blended Commerce , 2013, 2013 IEEE International Symposium on Industrial Electronics.

[4]  Arnold L. Rosenberg,et al.  Cellular ANTomata , 2007, Adv. Complex Syst..

[5]  Witold Pedrycz,et al.  Ambient Intelligence, Wireless Networking, And Ubiquitous Computing , 2006 .

[6]  Michael Friedewald,et al.  Privacy, identity and security in ambient intelligence: A scenario analysis , 2007, Telematics Informatics.

[7]  Mimmo Parente,et al.  The Firing Squad Synchronization Problem on Squares, Toruses and Rings , 2007, Int. J. Found. Comput. Sci..

[8]  Diane J. Cook,et al.  Author's Personal Copy Pervasive and Mobile Computing Ambient Intelligence: Technologies, Applications, and Opportunities , 2022 .

[9]  E. Kushilevitz.  Foundations of Cryptography Foundations of Cryptography , 2014 .

[10]  Hiroshi Umeo,et al.  A Seven-State Time-Optimum Square Synchronizer , 2010, ACRI.

[11]  Emiliano De Cristofaro,et al.  EsPRESSo: Efficient Privacy-Preserving Evaluation of Sample Set Similarity , 2012, DPM/SETOP.

[12]  Emiliano De Cristofaro,et al.  Experimenting with Fast Private Set Intersection , 2012, TRUST.

[13]  David Wright,et al.  The dark side of ambient intelligence , 2005 .

[14]  Emiliano De Cristofaro,et al.  (If) Size Matters: Size-Hiding Private Set Intersection , 2011, IACR Cryptol. ePrint Arch..

[15]  Mimmo Parente,et al.  Optimal Time and Communication Solutions of Firing Squad Synchronization Problems on Square Arrays, Toruses and Rings , 2004, Developments in Language Theory.

[16]  Seunghun Jin,et al.  A Location Privacy Protection Mechanism for Smart Space , 2003, WISA.

[17]  Thomas Ritz,et al.  Blended shopping: Interactivity and individualization , 2011, Proceedings of the International Conference on e-Business.

[18]  Hugo Krawczyk,et al.  HMAC: Keyed-Hashing for Message Authentication , 1997, RFC.

[19]  Arnold L. Rosenberg,et al.  Cellular ANTomata: Food-Finding and Maze-Threading , 2008, 2008 37th International Conference on Parallel Processing.

[20]  Margherita Napoli,et al.  Synchronization of a Line of Identical Processors at a Given Time , 1997, TAPSOFT.

[21]  Lionel M. Ni,et al.  The master key: a private authentication approach for pervasive computing environments , 2006, Fourth Annual IEEE International Conference on Pervasive Computing and Communications (PERCOM'06).

[22]  E. F. Moore.  The firing squad synchronization problem , 1964 .