SOCIAL NETWORKING WITH PROTECTING SENSITIVE LABELS USING ANONYMIZATION METHODOLOGY
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Abstract
The use of social network sites goes on increasing day by day e.g. wiki vote, live journal social network, twitter, LinkedIn network. By victimization these social networks, users get a lot of helpful data of alternative user’s like the user performance, non-public growth, spread of sickness, salaries etc. it's additionally vital that user’s non-public data shouldn't get reveal. Thus, nowadays it's essential to safeguard user’s privacy and utilization of social network information. the bulk of developer developed privacy models like K-anonymity for protecting node or vertex reidentification in structure data. User’s privacy models get forced by alternative user, if a bunch of node for the most part shares similar sensitive labels then new users simply establish recent user’s information, so solely structure anonymization technique isn't entirely protected or helpful.
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