PARTE : automatic program partitioning for efficient computation over encrypted data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.

Bibliographic Details
Main Author: Shah, Meelap (Meelap Vijay)
Other Authors: Nickolai Zeldovich.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2013
Subjects:
Online Access:http://hdl.handle.net/1721.1/79239
_version_ 1826209726877138944
author Shah, Meelap (Meelap Vijay)
author2 Nickolai Zeldovich.
author_facet Nickolai Zeldovich.
Shah, Meelap (Meelap Vijay)
author_sort Shah, Meelap (Meelap Vijay)
collection MIT
description Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.
first_indexed 2024-09-23T14:28:02Z
format Thesis
id mit-1721.1/79239
institution Massachusetts Institute of Technology
language eng
last_indexed 2024-09-23T14:28:02Z
publishDate 2013
publisher Massachusetts Institute of Technology
record_format dspace
spelling mit-1721.1/792392019-04-10T22:01:39Z PARTE : automatic program partitioning for efficient computation over encrypted data Shah, Meelap (Meelap Vijay) Nickolai Zeldovich. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (p. 45-47). Many modern applications outsource their data storage and computation needs to third parties. Although this lifts many infrastructure burdens from the application developer, he must deal with an increased risk of data leakage (i.e. there are more distributed copies of the data, the third party may be insecure and/or untrustworthy). Oftentimes, the most practical option is to tolerate this risk. This is far from ideal and in case of highly sensitive data (e.g. medical records, location history) it is unacceptable. We present PARTE, a tool to aid application developers in lowering the risk of data leakage. PARTE statically analyzes a program's source, annotated to indicate types which will hold sensitive data (i.e. data that should not be leaked), and outputs a partitioned version of the source. One partition will operate only on encrypted copies of sensitive data to lower the risk of data leakage and can safely be run by a third party or otherwise untrusted environment. The second partition must have plaintext access to sensitive data and therefore should be run in a trusted environment. Program execution will flow between the partitions, levaraging third party resources when data leakage risk is low. Further, we identify operations which, if efficiently supported by some encryption scheme, would improve the performance of partitioned execution. To demonstrate the feasiblity of these ideas, we implement PARTE in Haskell and run it on a web application, hpaste, which allows users to upload and share text snippets. The partitioned hpaste services web request 1.2 - 2.5 x slower than the original hpaste. We find this overhead to be moderately high. Moreover, the partitioning does not allow much code to run on encrypted data. We discuss why we feel our techniques did not produce an attractive partitioning and offer insight on new research directions which could yield better results. by Meelap Shah. S.M. 2013-06-17T19:49:50Z 2013-06-17T19:49:50Z 2013 2013 Thesis http://hdl.handle.net/1721.1/79239 845318813 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 47 p. application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Shah, Meelap (Meelap Vijay)
PARTE : automatic program partitioning for efficient computation over encrypted data
title PARTE : automatic program partitioning for efficient computation over encrypted data
title_full PARTE : automatic program partitioning for efficient computation over encrypted data
title_fullStr PARTE : automatic program partitioning for efficient computation over encrypted data
title_full_unstemmed PARTE : automatic program partitioning for efficient computation over encrypted data
title_short PARTE : automatic program partitioning for efficient computation over encrypted data
title_sort parte automatic program partitioning for efficient computation over encrypted data
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/79239
work_keys_str_mv AT shahmeelapmeelapvijay parteautomaticprogrampartitioningforefficientcomputationoverencrypteddata