WITHDRAWN: Data leak identification using scattering search K Means in social networks

Abstract

Abstract Social media can be a very effective communication source between the owner of data (the data generator) and the viewers (the end-users). This is effective in online communication that can result in virtual communities that make use of online social networks. The leakage of data (loss of data) refers to the security of information that describes information disclosure that is unwanted. Data leak prevention (DLP) means, either products or techniques for mitigating either some or all these threats. Such hierarchical techniques of clustering can be a very popular technique of clustering observed in Machine Learning. K-means clustering is a popular technique for achieving partitioned clustering. Hierarchical clustering can be deterministic in nature with a lower efficiency of execution time compared to the clustering that is partitioned owing to complexity. This work investigated the proposed Scattering Search K Means (SS-K Means) Clustering which is based on Stochastic Diffusion Search (SDS) K Means clustering technique for finding optimal clustering points.