Bharath K. Samanthula

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For the past decade, query processing on relational data has been studied extensively, and many theoretical and practical solutions to query processing have been proposed under various scenarios. With the recent popularity of cloud computing, users now have the opportunity to outsource their data as well as the data management tasks to the cloud. However,(More)
Data Mining has wide applications in many areas such as banking, medicine, scientific research and among government agencies. Classification is one of the commonly used tasks in data mining applications. For the past decade, due to the rise of various privacy issues, many theoretical and practical solutions to the classification problem have been proposed(More)
Due to cost-efficiency and less hands-on management, data owners are outsourcing their data to the cloud which can provide access to the data as a service. However, by outsourcing their data to the cloud, the data owners lose control over their data as the cloud provider becomes a third party. At first, encrypting the data by the owner and then exporting it(More)
Wireless sensor networks (WSNs) have wide range of applications in military, health-monitoring, smart-home applications, and in other commercial environments. The computation of data aggregation functions like MIN/MAX is one of the commonly used tasks in many such WSN applications. However, due to privacy issues in some of these applications, the individual(More)
With the growing popularity of data and service outsourcing, where the data resides on remote servers in encrypted form, there remain open questions about what kind of query operations can be performed on the encrypted data. In this paper, we focus on one such important query operation, namely range query. One of the basic security primitive that can be(More)
In the last decade, several techniques have been proposed to evaluate different types of queries (e.g., range and aggregate queries) over encrypted data in a privacy-preserving manner. However, solutions supporting the privacypreserving evaluation of complex queries over encrypted data have been developed only recently. Such recent techniques, however, are(More)
Many techniques for privacy-preserving data mining (PPDM) have been investigated over the past decade. Such techniques, however, usually incur heavy computational and communication cost on the participating parties and thus entities with limited resources may have to refrain from participating in the PPDM process. To address this issue, one promising(More)
Many secure data analysis tasks, such as secure clustering and classification, require efficient mechanisms to convert the intermediate encrypted integers into the corresponding encryptions of bits. The existing bit-decomposition algorithms either do not offer sufficient security or are computationally inefficient. In order to provide better security as(More)