On preserving privacy in cloud computing using ToR

A. Carnielli, M. Aiash, M. Alazab

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The Internet allows for an efficient, inexpensive collection of information without surfers' consents. This includes surfers' preferences, interests or even credit card information. Furthermore, it is well known that some oppressive governments filter the information that can digitally reach their countries. Also, there are evidences that certain governments spy on citizens and organizations through intercepting phone calls, activities on social media and blogs. For Internet browsing, several methods of privacy-preserving and anonymizers have been developed. An example of such a technology is The Onion Router (ToR) network, which has been proven to guarantee users' anonymity and privacy while they are browsing the Internet. However, with the wide deployment of virtualization solutions and the tremendous migration to cloud-based services, many online services have moved onto the cloud. This situation complicates the issue of preserving a client's privacy and anonymity and raises a "question mark" as to the efficiency of current anonymizers in this new environment. To the best of our knowledge, few studies have been conducted to analyze the compatibility between the ToR network and this new emerging infrastructure. This paper presents a qualitative analysis of the feasibility and efficiency of the ToR in cloud infrastructure and the possibility of integrating these technologies.

Original languageEnglish
Title of host publicationPervasive Computing
Subtitle of host publicationNext Generation Platforms for Intelligent Data Collection
Place of PublicationUK
PublisherElsevier
Chapter1
Pages3-25
Number of pages23
ISBN (Electronic)9780128037027
ISBN (Print)9780128036631
DOIs
Publication statusPublished - 13 Apr 2016

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    Carnielli, A., Aiash, M., & Alazab, M. (2016). On preserving privacy in cloud computing using ToR. In Pervasive Computing: Next Generation Platforms for Intelligent Data Collection (pp. 3-25). Elsevier. https://doi.org/10.1016/B978-0-12-803663-1.00001-2