HIKE: Walking the Privacy Trail
Paper in proceedings, 2018

We consider the problem of privacy-preserving processing of outsourced data in the context of user-customised services. Clients store their data on a server. In order to provide user-dependent services, service providers may ask the server to compute functions on the users’ data. We propose a new solution to this problem that guarantees data privacy (i.e., an honest-but-curious server cannot access plaintexts), as well as that service providers can correctly decrypt only –functions on– the data the user gave them access to (i.e., service providers learn nothing more than the result of user-selected computations). Our solution has as base point a new secure labelled homomorphic encryption scheme (LEEG). LEEG supports additional algorithms (FEET) that enhance the scheme’s functionalities with extra privacy-oriented fea- tures. Equipped with LEEG and FEET, we define HIKE: a lightweight protocol for private and secure storage, computation and disclosure of users’ data. Finally, we implement HIKE and benchmark its performances demonstrating its succinctness and efficiency.

Labeled Homomorphic Encryption

Privacy-preserving computation.

GDPR

Author

Elena Pagnin

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Carlo Brunetta

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Pablo Picazo-Sanchez

University of Gothenburg

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 11124 LNCS 43-66

17th International Conference on Cryptology And Network Security
Naples, Italy,

PRECIS: Privacy and security in wearable computing devices

Swedish Research Council (VR), 2015-01-01 -- 2018-12-31.

Subject Categories

Communication Systems

Computer Science

Computer Systems

DOI

10.1007/978-3-030-00434-7_3

More information

Latest update

1/21/2019