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Content Provider | IEEE Xplore Digital Library |
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Author | Srivastava, A. Geethakumari, G. |
Copyright Year | 2013 |
Description | Author affiliation: Dept. of Comput. Sci. & Inf. Syst., BITS Pilani, Hyderabad, India (Srivastava, A.; Geethakumari, G.) |
Abstract | Online Social Networking has gained huge popularity amongst the masses. It is common for the users of Online Social Networks (OSNs) to share information with digital friends but in the bargain they loose privacy. Users are unaware of the privacy risks involved when they share their sensitive information in the network. The users should be aware of their privacy quotient and should know where they stand in the privacy measuring scale. In this paper we have described and calculated the Privacy Quotient i.e a privacy metric to measure the privacy of the user's profile using the naive approach. In the starting of the paper we have given the detailed analysis of the survey that we have carried out to know how well do people understand privacy in online social networks. At last we have proposed a model that will ensure privacy in the unstructured data. It will make use of the Item Response Theory model to measure the privacy leaks in the messages and text that is being posted by the users of the online social networking sites. |
Starting Page | 2095 |
Ending Page | 2100 |
File Size | 471080 |
Page Count | 6 |
File Format | |
ISBN | 9781479924325 |
e-ISBN | 9781467362177 |
DOI | 10.1109/ICACCI.2013.6637504 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-08-22 |
Publisher Place | India |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Privacy Data privacy Sensitivity Social network services Unstructured data privacy Social networks Data models Electronic mail Privacy quotient Mathematical model |
Content Type | Text |
Resource Type | Article |
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