PRISM - Privacy-Preserving Search in MapReduce

Blass, Erik-Oliver; Di Pietro, Roberto; Molva, Refik; Önen, Melek
PETS 2012, 12th Privacy Enhancing Technologies Symposium, July 11-13, 2012, Vigo, Spain / Also published in LNCS, Volume 7384/2012, Springer

We present PRISM, a privacy-preserving scheme for word search in cloud computing. In the face of a curious cloud provider, the main challenge is to design a scheme that achieves privacy while preserving the efficiency of cloud computing. Solutions from related research, like encrypted keyword search or Private Information Retrieval (PIR), fall short of meeting real-world cloud requirements and are impractical. PRISM’s idea is to transform the problem of word search into a set of parallel instances of PIR on small datasets. Each PIR

instance on a small dataset is efficiently solved by a node in the cloud during the “Map” phase of MapReduce. Outcomes of map computations are then aggregated during the “Reduce” phase. Due to the linearity of PRISM, the simple aggregation of map results yields the final output of the word search operation. We have implemented PRISM on Hadoop MapReduce and evaluated its efficiency using real-world DNS logs. PRISM’s overhead over non-private search is only 11%. Thus, PRISM offers privacy-preserving search that meets cloud computing efficiency requirements. Moreover, PRISMis compatible with standard MapReduce, not requiring any change to the interface or infrastructure.


DOI
Type:
Conférence
City:
Vigo
Date:
2012-07-11
Department:
Sécurité numérique
Eurecom Ref:
3718
Copyright:
© Springer. Personal use of this material is permitted. The definitive version of this paper was published in PETS 2012, 12th Privacy Enhancing Technologies Symposium, July 11-13, 2012, Vigo, Spain / Also published in LNCS, Volume 7384/2012, Springer and is available at : http://dx.doi.org/10.1007/978-3-642-31680-7_10

PERMALINK : https://www.eurecom.fr/publication/3718