Multimodal Indexable Encryption for Mobile Cloud-Based Applications

Bernardo Ferreira, Joao Leitao, Henrique Domingos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper we propose MIE, a Multimodal Indexable Encryption framework that for the first time allows mobile applications to securely outsource the storage and search of their multimodal data (i.e. data containing multiple media formats) to public clouds with privacy guarantees. MIE is designed as a distributed framework architecture, leveraging on shared cloud repositories that can be accessed simultaneously by multiple users. At its core MIE relies on Distance Preserving Encodings (DPE), a novel family of encoding algorithms with cryptographic properties that we also propose. By applying DPE to multimodal data features, MIE enables high-cost clustering and indexing operations to be handled by cloud servers in a privacy-preserving way. Experiments show that MIE achieves better performance and scalability when compared with the state of art, with measurable impact on mobile resources and battery life.

Original languageEnglish
Title of host publicationProceedings - 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017
PublisherIEEE Computer Society
Pages213-224
Number of pages12
ISBN (Electronic)9781538605417
DOIs
Publication statusPublished - 2017
Event47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017 - Denver, United States
Duration: 26 Jun 201729 Jun 2017

Conference

Conference47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017
CountryUnited States
CityDenver
Period26/06/1729/06/17

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  • Cite this

    Ferreira, B., Leitao, J., & Domingos, H. (2017). Multimodal Indexable Encryption for Mobile Cloud-Based Applications. In Proceedings - 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017 (pp. 213-224). [8023124] IEEE Computer Society. https://doi.org/10.1109/DSN.2017.31