Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/1062745.1062886acmconferencesArticle/Chapter ViewAbstractPublication PagesthewebconfConference Proceedingsconference-collections
Article

Enhancing the privacy of web-based communication

Published: 10 May 2005 Publication History

Abstract

A profiling adversary is an adversary whose goal is to classify a population of users into categories according to messages they exchange. This adversary models the most common privacy threat against web based communication.We propose a new encryption scheme, called stealth encryption, that protects users from profiling attacks by concealing the semantic content of plaintext while preserving its grammatical structure and other non-semantic linguistic features, such as word frequency distribution. Given English plaintext, stealth encryption produces ciphertext that cannot efficiently be distinguished from normal English text (our techniques apply to other languages as well).

References

[1]
R. Kaplan, S. Riezler, T.H. King, J.T. Maxwell, and A. Vasserman. Speed and accuracy in shallow and deep stochastic parsing. In HLT-NAACL, 2004.
[2]
M. Chapman and G. Davida. Hiding the hidden: A software system for concealing ciphertext in innocuous text. In ICIS, volume 1334, Beijing, China, 11--14 1997.
[3]
T. E. Dunning. Accurate methods for the statistics of surprise and coincidence. Computational Linguistics, 19(1):61--74, 1993.
[4]
C. Dwork and M. Naor. Pricing via processing or combatting junk mail. In CRYPTO 92 Proceedings, volume 740 of Lecture Notes in Computer Science, 1992.
[5]
P. Golle and A. Farahat. Defending email communication against profiling attack. In Workshop on Privacy in the Electronic Society, WPES-2004, October 2004.
[6]
P. Wayner. Mimic functions. CRYPTOLOGIA, 16(3):193--214, July 1992.

Index Terms

  1. Enhancing the privacy of web-based communication

      Recommendations

      Reviews

      Zakaria Saleh

      Stealth encryption, a new encryption scheme that should protect users from profiling attacks by concealing the semantic content of plaintext, while preserving its grammatical structure and other nonsemantic linguistic features, is proposed in this paper. This encryption scheme produces ciphertext that cannot efficiently be distinguished from normal English text; every word of English plaintext is replaced with a word of ciphertext drawn from an English dictionary. The techniques apply to other languages as well. The paper provides an example of an encrypted message, and then explains the process of the encryption. Compared to other lexical steganography methods, such as mimic functions, stealth encryption does not require any key exchange. The authors also state that stealth encryption is much more efficient, explaining that the ciphertext generated by stealth encryption is about the same size as the original text, where the average size of the ciphertext generated by nicetext is 30 times the size of the original text. The paper is intended to introduce a new protocol for encryption. However, without providing more details, it is hard to evaluate or express a professional opinion. Looking at the data provided to illustrate the test results of the proposed encryption scheme, I find this work to be of great significance; it should contribute to enhancing the privacy of Web-based communication with greater efficiency. Online Computing Reviews Service

      Access critical reviews of Computing literature here

      Become a reviewer for Computing Reviews.

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      WWW '05: Special interest tracks and posters of the 14th international conference on World Wide Web
      May 2005
      454 pages
      ISBN:1595930515
      DOI:10.1145/1062745
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 10 May 2005

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. privacy
      2. profiling
      3. protection

      Qualifiers

      • Article

      Acceptance Rates

      Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • 0
        Total Citations
      • 350
        Total Downloads
      • Downloads (Last 12 months)1
      • Downloads (Last 6 weeks)0
      Reflects downloads up to 03 Oct 2024

      Other Metrics

      Citations

      View Options

      Get Access

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media