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New Approach to Quantification of Privacy on Social Network Sites IEEE AINA 2010 Tran Hong Ngoc Isao Echizen Kamiyama Komei Hiroshi Yoshiura VNU, Vietnam NII, Japan UEC, Japan UEC, Japan Presenter: Yu-Song Syu Social Network Sites Growth of SNSs Leads to an explosion in online informationsharing With SNSs People share information with friends Information include sensitive data Location, age, career, … Intruders in SNSs By making statistics, Intruders may achieve personal information: Commercial purpose Identity theft Physical harm … How to get such information? http://www.iis.sinica.edu.tw http://www.iis.sinica.edu.tw Usually, people do not know How Much private information they reveal about themselves and others Privacy Metric Based on probability and entropy Helps user know how much private information may leak from their blog sentences Defines the Leaked Privacy Value, Δ, as the amount of knowledge that intruders can learn about a “problem of interest” Proposed System Model Info. Retrieval techniques based on NLP methods Quantification of Privacy System Model Find the information about someone Prefecture, age, city, university, … Blog sentences that users post Event Event & Blog Set BlogSetj BlogSeti Event: ( k ) x | x U ,0 p( x) 1 Blog Set: (k ) i x | x (k ) ,0 p( x) 1 , (k ) i (k ) Intersection: ~ ( k ) x | 0 p( x) 1, x 1k , x 2k ,..., x nk n i 1 Blog Set / Joint Blog Set Assumed to never be empty Example: Prefecture Before Proposed Metric… Math Backgrounds Entropy (Uncertainty) Event Conditional Entropy Joint Entropy Possible Value Why Use Entropy? Idea: Difference of Uncertainty Leaked Privacy Privacy Leakage Metric Leaked Privacy Value: The change in the privacy value that is had by subtracting the privacy after sentences are posted from the privacy before the sentences are posted before (k ) after (k ) H ({ }) H ({~ }) # events H ({ ( k ) }) H ( (1) , ( 2) ,..., ( m) ) ,& H ({~ ( k ) }) H ( ~(1) , ~ ( 2) ,..., ~ ( m) ) Experiments Dataset: Statistical Survey Department, Statistics Bureau, Ministry of Internal Affairs and Communications Problem of Interest: Gaining information relating to a victim in an accident, which happened in Japan’s subway and were discussed by SNS users Experiments - Prefecture Experiments - Age (Age) Prefecture Age Experiments – Total Leaked Privacy Total Leaked Privacy Before & After Blogging Conclusions Proposed a new metric to quantify how much private information is leaked from blog on SNSs SNS users can see if the posting carelessly expose private information Based on probability and entropy, the proposal is simpler then others but effective, as proved in experiments