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There are multiple papers published by Arvind and Vitaly (De-anonymising social network) and other papers about de-anonymising social networks. In short, they used a network graph to deanonymise an anonymous network graph with some known seeds. There are also papers that are seedless. However, none of the papers I have read offered any defences against these attacks.

My question is: is it possible to release an anonymous network graph (raw data) that are resistant to these attacks (e.g. network topology attacks and edge privacy attacks).

I've been told that instead of releasing the actual raw data anonymous graph, you should allow query to the data and release the statistical table

  • There is a topic in computational learning theory called "learning by statistical query." You might want to cross check against research in that field before assuming this provides more security. – djechlin Feb 23 '17 at 15:26

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