Title page for ETD etd-122310-144743

Document Type thesis

Author Name Naryshkin, Konstantin

URN etd-122310-144743

Title Study on the Leakage of Private User Information Via a Range of Popular Websites

Degree MS

Department Computer Science

Advisors
Craig Wills, Advisor
Kathryn Fisler, Reader

Keywords
Personally Identifiable Information
Privacy

Date of Presentation/Defense 2010-12-13

Availability unrestricted

Abstract
On the modern web, many sites have third party content, be it through maps, embedded objects, ads, or through other types. Users pay little attention to the source of this content since it is such a common occurrence. Unfortunately, this content can be an avenue for third parties to discover private information about the user. Previous work has found these types of leaks in social networking sites. By logging headers during the usage of 120 sites across 12 major categories, we were able to find leakage of a user’s private information occurring on many other types of popular web sites. We found leakage on 75% of the sites we looked at and at least one instance in each of the categories. Based on the leaks we found, we propose a classification of the types of leakage that can occur via the HTTP header and use this system to analyze our results.

Files
naryshkin.pdf

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Document Type	thesis
Author Name	Naryshkin, Konstantin
URN	etd-122310-144743
Title	Study on the Leakage of Private User Information Via a Range of Popular Websites
Degree	MS
Department	Computer Science
Advisors	Craig Wills, Advisor Kathryn Fisler, Reader
Keywords	Personally Identifiable Information Privacy
Date of Presentation/Defense	2010-12-13
Availability	unrestricted
Abstract On the modern web, many sites have third party content, be it through maps, embedded objects, ads, or through other types. Users pay little attention to the source of this content since it is such a common occurrence. Unfortunately, this content can be an avenue for third parties to discover private information about the user. Previous work has found these types of leaks in social networking sites. By logging headers during the usage of 120 sites across 12 major categories, we were able to find leakage of a user’s private information occurring on many other types of popular web sites. We found leakage on 75% of the sites we looked at and at least one instance in each of the categories. Based on the leaks we found, we propose a classification of the types of leakage that can occur via the HTTP header and use this system to analyze our results.
Files	naryshkin.pdf