Detecting unintentional information leakage in social media news comments

Inbal Yahav; David G. Schwartz; Gahl Silverman

doi:10.1109/IRI.2014.7051874

Detecting unintentional information leakage in social media news comments

Inbal Yahav, David G. Schwartz, Gahl Silverman

School of Business Administration

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

This paper is concerned with unintentional information leakage (UIL) through social networks, and in particular, Facebook Organizations often use forms of self censorship in order to maintain security. Non-identification of individuals, products, or places is seen as a sufficient means of information protection. A prime example is the replacement of a name with a supposedly non-identifying initial. This has traditionally been effective in obfuscating the identity of military personnel, protected witnesses, minors, victims or suspects who need to be granted a level of protection through anonymity. We challenge the effectiveness of this form of censorship in light of current uses and ongoing developments in Social Networks showing that name-obfits cation mandated by court or military order can be systematically compromised through the unintentional actions of public social network commenters. We propose a qualitative method for recognition and characterization of UIL followed by a quantitative study that automatically detects UIL comments.

Original language	English
Title of host publication	Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014
Editors	Elisa Bertino, Bhavani Thuraisingham, Ling Liu, James Joshi
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	74-79
Number of pages	6
ISBN (Electronic)	9781479958801
DOIs	https://doi.org/10.1109/IRI.2014.7051874
State	Published - 27 Feb 2014
Event	15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014 - San Francisco, United States Duration: 13 Aug 2014 → 15 Aug 2014

Publication series

Name	Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014

Conference

Conference	15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014
Country/Territory	United States
City	San Francisco
Period	13/08/14 → 15/08/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

Censorship
Comments
Online news
Privacy
Social media
Social networks
Text mining
Unintentional information leakage

Access to Document

10.1109/IRI.2014.7051874

Cite this

Yahav, I., Schwartz, D. G., & Silverman, G. (2014). Detecting unintentional information leakage in social media news comments. In E. Bertino, B. Thuraisingham, L. Liu, & J. Joshi (Eds.), Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014 (pp. 74-79). [7051874] (Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IRI.2014.7051874

Yahav, Inbal ; Schwartz, David G. ; Silverman, Gahl. / Detecting unintentional information leakage in social media news comments. Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014. editor / Elisa Bertino ; Bhavani Thuraisingham ; Ling Liu ; James Joshi. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 74-79 (Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014).

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author = "Inbal Yahav and Schwartz, {David G.} and Gahl Silverman",

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Yahav, I, Schwartz, DG & Silverman, G 2014, Detecting unintentional information leakage in social media news comments. in E Bertino, B Thuraisingham, L Liu & J Joshi (eds), Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014., 7051874, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014, Institute of Electrical and Electronics Engineers Inc., pp. 74-79, 15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014, San Francisco, United States, 13/08/14. https://doi.org/10.1109/IRI.2014.7051874

Detecting unintentional information leakage in social media news comments. / Yahav, Inbal; Schwartz, David G.; Silverman, Gahl.
Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014. ed. / Elisa Bertino; Bhavani Thuraisingham; Ling Liu; James Joshi. Institute of Electrical and Electronics Engineers Inc., 2014. p. 74-79 7051874 (Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper is concerned with unintentional information leakage (UIL) through social networks, and in particular, Facebook Organizations often use forms of self censorship in order to maintain security. Non-identification of individuals, products, or places is seen as a sufficient means of information protection. A prime example is the replacement of a name with a supposedly non-identifying initial. This has traditionally been effective in obfuscating the identity of military personnel, protected witnesses, minors, victims or suspects who need to be granted a level of protection through anonymity. We challenge the effectiveness of this form of censorship in light of current uses and ongoing developments in Social Networks showing that name-obfits cation mandated by court or military order can be systematically compromised through the unintentional actions of public social network commenters. We propose a qualitative method for recognition and characterization of UIL followed by a quantitative study that automatically detects UIL comments.

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Yahav I, Schwartz DG, Silverman G. Detecting unintentional information leakage in social media news comments. In Bertino E, Thuraisingham B, Liu L, Joshi J, editors, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 74-79. 7051874. (Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014). doi: 10.1109/IRI.2014.7051874

Detecting unintentional information leakage in social media news comments

Abstract

Publication series

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Bibliographical note

Keywords

Access to Document

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