FriendGuard: A friend search engine with guaranteed friend exposure degree

Joshua Morris, Dan Lin, Anna Squicciarini

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

Abstract

With the prevalence of online social networking, a large amount of studies have focused on online users' privacy. Existing work has heavily focused on preventing unauthorized access of one's personal information (e.g. locations, posts and photos). Very little research has been devoted into protecting the friend search engine, a service that allows people to explore others' friend lists. Although most friend search engines only disclose a partial view of one's friend list (e.g., k friends) or offer the ability to show all or no friends, attackers may leverage the combined knowledge from views obtained from different queries to gain a much larger social network of a targeted victim, potentially revealing sensitive information of a victim. In this paper, we propose a new friend search engine, namely FriendGuard, which guarantees the degree of friend exposure as set by users. If a user only allows k of his/her friends to be disclosed, our search engine will ensure that any attempts of discovering more friends of this user through querying the user's other friends will be a failure. The key idea underlying our search engine is the construction of a unique sub social network that is capable of satisfying query needs as well as controlling the degree of friend exposure. We have carried out an extensive experimental study and the results demonstrate both efficiency and effectiveness in our approach.

Original languageEnglish (US)
Title of host publicationSACMAT 2019 - Proceedings of the 24th ACM Symposium on Access Control Models and Technologies
PublisherAssociation for Computing Machinery
Pages37-48
Number of pages12
ISBN (Electronic)9781450367530
DOIs
StatePublished - May 28 2019
Event24th ACM Symposium on Access Control Models and Technologies, SACMAT 2019 - Toronto, Canada
Duration: Jun 3 2019Jun 6 2019

Publication series

NameProceedings of ACM Symposium on Access Control Models and Technologies, SACMAT

Conference

Conference24th ACM Symposium on Access Control Models and Technologies, SACMAT 2019
CountryCanada
CityToronto
Period6/3/196/6/19

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All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality
  • Information Systems

Cite this

Morris, J., Lin, D., & Squicciarini, A. (2019). FriendGuard: A friend search engine with guaranteed friend exposure degree. In SACMAT 2019 - Proceedings of the 24th ACM Symposium on Access Control Models and Technologies (pp. 37-48). (Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT). Association for Computing Machinery. https://doi.org/10.1145/3322431.3325103
Morris, Joshua ; Lin, Dan ; Squicciarini, Anna. / FriendGuard : A friend search engine with guaranteed friend exposure degree. SACMAT 2019 - Proceedings of the 24th ACM Symposium on Access Control Models and Technologies. Association for Computing Machinery, 2019. pp. 37-48 (Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT).
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abstract = "With the prevalence of online social networking, a large amount of studies have focused on online users' privacy. Existing work has heavily focused on preventing unauthorized access of one's personal information (e.g. locations, posts and photos). Very little research has been devoted into protecting the friend search engine, a service that allows people to explore others' friend lists. Although most friend search engines only disclose a partial view of one's friend list (e.g., k friends) or offer the ability to show all or no friends, attackers may leverage the combined knowledge from views obtained from different queries to gain a much larger social network of a targeted victim, potentially revealing sensitive information of a victim. In this paper, we propose a new friend search engine, namely FriendGuard, which guarantees the degree of friend exposure as set by users. If a user only allows k of his/her friends to be disclosed, our search engine will ensure that any attempts of discovering more friends of this user through querying the user's other friends will be a failure. The key idea underlying our search engine is the construction of a unique sub social network that is capable of satisfying query needs as well as controlling the degree of friend exposure. We have carried out an extensive experimental study and the results demonstrate both efficiency and effectiveness in our approach.",
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Morris, J, Lin, D & Squicciarini, A 2019, FriendGuard: A friend search engine with guaranteed friend exposure degree. in SACMAT 2019 - Proceedings of the 24th ACM Symposium on Access Control Models and Technologies. Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT, Association for Computing Machinery, pp. 37-48, 24th ACM Symposium on Access Control Models and Technologies, SACMAT 2019, Toronto, Canada, 6/3/19. https://doi.org/10.1145/3322431.3325103

FriendGuard : A friend search engine with guaranteed friend exposure degree. / Morris, Joshua; Lin, Dan; Squicciarini, Anna.

SACMAT 2019 - Proceedings of the 24th ACM Symposium on Access Control Models and Technologies. Association for Computing Machinery, 2019. p. 37-48 (Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT).

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

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Morris J, Lin D, Squicciarini A. FriendGuard: A friend search engine with guaranteed friend exposure degree. In SACMAT 2019 - Proceedings of the 24th ACM Symposium on Access Control Models and Technologies. Association for Computing Machinery. 2019. p. 37-48. (Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT). https://doi.org/10.1145/3322431.3325103