Saptarshi Chakraborty

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We propose an (α, k) anonymity model based on the eigenvector centrality value of the nodes present in the raw graph and further extend it to propose (α, l) diversity model and recursive (α, c, l) diversity model which can handle the protection of the sensitive attributes associated with a particular actor. For anonymization purpose, we(More)
Large amounts of data generated everyday by different organizations for various purposes have catalyzed research opportunities related to data science. Publishing raw data may raise security concerns among the users or actors who have provided some sensitive information in the raw data. Over the years, it has been observed that attackers can very easily(More)
Rapid growth and development of social networks has attracted the interest of the scientific community to utilize these huge datasets for research purpose. However, preserving the privacy of the users in the published data has also become an important concern. An adversary with very little background knowledge about the actors can extract personal(More)
We propose an (a, k) anonymity model based on the eigenvector centrality value of the nodes present in the raw graph and further extend it to propose (a, l) diversity model and recursive (a, c, l) diversity model which can handle the protection of the sensitive attributes associated with a particular actor. For anonymization purpose, we applied noise node(More)
Protecting the identities of the actors along with their sensitive information has become a matter of concern for the organizations which are publishing huge amounts of data every day for the purpose of research. Recent studies have shown that simply removing the sensitive labels associated with the actors do not guarantee their privacy protection. The(More)
Advances in technology have brought about extensive research in the field of image fusion. Image fusion is one of the most researched challenges of Face Recognition. Face Recognition (FR) is the process by which the brain and mind understand, interpret and identify or verify human faces.. Image fusion is the combination of two or more source images which(More)
Advances in technology have brought about extensive research in the field of image fusion. Image fusion is one of the most researched challenges of Face Recognition. Face Recognition (FR) is the process by which the brain and mind understand, interpret and identify or verify human faces Face recognition is nothing but a biometric application by which we can(More)
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