Auditable Compressed Storage

Iraklis Leontiadis, Reza Curtmola

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

Abstract

Outsourcing data to the cloud for personal use is becoming an everyday trend rather than an extreme scenario. The frequent outsourcing of data increases the possible attack window because users do not fully control their personal files. Typically, once there are established secure channels between two endpoints, communication is considered secure. However, in the cloud model the receiver–the cloud–cannot be fully trusted, either because it has been under adversarial control, or because it acts maliciously to increase its revenue by deleting infrequent accessed file blocks. One approach used by current literature to address the aforementioned security concerns is via Remote Data Integrity Checking (RDIC) protocols, whereby a data owner can challenge an untrusted cloud service provider (CSP) to prove faithful storage of its data. Current RDIC protocols assume that the original data format remains unchanged. However, users may wish to compress their data in order to enjoy less charges. In that case, current RDIC protocols become impractical because, each time compression happens on a file, the user has to run a new RDIC protocol. In this work we initiate the study for Auditable Compressed Storage (ACS). After defining the new model we instantiate two protocols for different widely used compression techniques: run length encoding and Huffman encoding. In contrast with conventional RDIC, our protocols allow a user to delegate the compression to the cloud in a provably secure way: The client can verify correctness of compression without having to download the entire uncompressed file and check it against the compressed one.

Original languageEnglish (US)
Title of host publicationInformation Security - 22nd International Conference, ISC 2019, Proceedings
EditorsZhiqiang Lin, Charalampos Papamanthou, Michalis Polychronakis
PublisherSpringer Verlag
Pages67-86
Number of pages20
ISBN (Print)9783030302146
DOIs
StatePublished - 2019
Event22nd International Conference on Information Security, ISC 2019 - New York City, United States
Duration: Sep 16 2019Sep 18 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11723 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Information Security, ISC 2019
CountryUnited States
CityNew York City
Period9/16/199/18/19

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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