Back to results

University of Kansas

Arcana: Private tweets on a public microblog platform

Abstract

dc:description.abstract

As one of the world’s most famous online social networks (OSN), Twitter now has 320 million monthly active users. Accompanying the large user group and abundant personal information, users increasingly realize the vulnerability of tweets and have reservations of showing certain tweets to different follower groups, such as colleagues, friends and other followers. However, Twitter does not offer enough privacy protection or access control functions. Users can just set an account as protected, which results in only the user’s followers seeing the tweet. The protected tweet does not appear in the public domain, third party sites and search engines cannot access the tweet. However, a protected account cannot distinguish between different follower groups or users who use multiple accounts. To serve the demand of the user so that they can restrict the access of each tweet to certain follower groups, we propose a browser plug-in system, which utilizes CP-ABE (Ciphertext Policy Attribute based encryption), allowing the user to select followers based on predefined attributes. Through simple installation and pre-setting, the user can encrypt and decrypt tweets conveniently and can avoid the fear of information leakage.

Degree

thesis:*
Grantor dc:publisher
University of Kansas
Year dc:date.issued
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Narasimman, Anirudh
Advisor dc:contributor.advisor
  • Luo, Bo

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • Copyright held by the author.
Language dc:language.iso
en

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:kuscholarworks.ku.edu:1808/23921

Chain of custody

source
Harvested from
University of Kansas
Base URL
kuscholarworks.ku.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Narasimman, Anirudh. Arcana: Private tweets on a public microblog platform. University of Kansas, 2016. http://hdl.handle.net/1808/23921