Data Security and Anonymization in Neighborhood Attacks in Clustered Network in Internet of Things (NIoT)

In this paper author tries to focus on the review on the K Nearest Neighbor (KNN) tied by one or more specific types of inter dependency, such as values, visions, ideas, financial exchange, friendship, conflict, or trade. Social network analysis views social relationships in terms of nodes and ties. It also focuses the network analysis, application as well as problem statement. In this paper presents a outline for the privacy hazard and sharing the anonymized data in the network. This includes a proposed architecture design flow, for which the author considers the several variations and make connections. On several real-world social networks, we show that simple anonymization techniques are inadequate, it results in considerable breaks of privacy for even modestly informed opponents. It also concentrates on a new anonymization technique. It based on the network and validate analytically that leads to saving of the privacy threat. It also analyses the effect that anonymizing the network has on the utility of the data for social network analysis.