Paper 2015/1194 Original: eprint.iacr.org/2015/1194 ↗
HOMOMORPHIC AUTOCOMPLETE
Abstract
With the rapid progress in fully homomorpic encryption (FHE) and somewhat homomorphic encryption (SHE) schemes, we are wit- nessing renewed efforts to revisit privacy preserving protocols. Several works have already appeared in the literature that provide solutions to these problems by employing FHE or SHE techniques. These applications range from cloud computing to computation over confidential patient data to several machine learning problems such as classifying privatized data. One application where privacy is a major concern is web search – a task carried out on a daily basis by billions of users around the world. In this work, we focus on a more surmountable yet essential version of the search problem, i.e. autocomplete. By utilizing a SHE scheme we propose concrete solutions to a homomorphic autocomplete problem. To investigate the real-life viability, we tackle a number of problems in the way towards a practical implementation such as communication and computational efficiency.
Metadata
- Available format(s)
PDF- Category
- Applications
- Publication info
- Preprint.
- History
- 2015-12-16: last updated
- 2015-12-16: published
- Short URL
- https://ia.cr/2015/1194
- License
- https://creativecommons.org/licenses/by/4.0/
BibTeX
@misc{cryptoeprint:2015/1194,
author = {Gizem S. Çetin and Wei Dai and Yarkın Doröz and Berk Sunar},
title = {HOMOMORPHIC AUTOCOMPLETE},
howpublished = {Cryptology {ePrint} Archive, Paper 2015/1194},
year = {2015},
url = {https://eprint.iacr.org/2015/1194}
}