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학술논문KSII Transactions on Internet and Information Systems2016.07 발행KCI 피인용 1

Unintentional and Involuntary Personal Information Leakage on Facebook from User Interactions

Unintentional and Involuntary Personal Information Leakage on Facebook from User Interactions

Po-Ching Lin(National Chung Cheng University, Taiwan); Pei-Ying Lin(HTC Corporation, Taiwan)

10권 7호, 3301~3318쪽

초록

Online social networks (OSNs) have changed the way people communicate with each other. An OSN usually encourages the participants to provide personal information such as real names, birthdays and educational background to look for and establish friendships among them. Some users are unwilling to reveal personal information on their personal pages due to potential privacy concerns, but their friends may inadvertently reveal that. In this work, we investigate the possibility of leaking personal information on Facebook in an unintentional and involuntary manner. The revealed information may be useful to malicious users for social engineering and spear phishing. We design the inference methods to find birthdays and educational background of Facebook users based on the interactions among friends on Facebook pages and groups, and also leverage J-measure to find the inference rules. The inference improves the finding rate of birthdays from 71.2% to 87.0% with the accuracy of 92.0%, and that of educational background from 75.2% to 91.7% with the accuracy of 86.3%. We also suggest the sanitization strategies to avoid the private information leakage.

Abstract

Online social networks (OSNs) have changed the way people communicate with each other. An OSN usually encourages the participants to provide personal information such as real names, birthdays and educational background to look for and establish friendships among them. Some users are unwilling to reveal personal information on their personal pages due to potential privacy concerns, but their friends may inadvertently reveal that. In this work, we investigate the possibility of leaking personal information on Facebook in an unintentional and involuntary manner. The revealed information may be useful to malicious users for social engineering and spear phishing. We design the inference methods to find birthdays and educational background of Facebook users based on the interactions among friends on Facebook pages and groups, and also leverage J-measure to find the inference rules. The inference improves the finding rate of birthdays from 71.2% to 87.0% with the accuracy of 92.0%, and that of educational background from 75.2% to 91.7% with the accuracy of 86.3%. We also suggest the sanitization strategies to avoid the private information leakage.

발행기관:
한국인터넷정보학회
DOI:
http://dx.doi.org/10.3837/tiis.2016.07.024
분류:
컴퓨터학

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Unintentional and Involuntary Personal Information Leakage on Facebook from User Interactions | KSII Transactions on Internet and Information Systems 2016 | AskLaw | 애스크로 AI