Conference Papers

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    A scalable cloud platform using matlab distributed computing server integrated with HDFS
    (IEEE Computer Society help@computer.org, 2012) Dutta, R.; Annappa, B.
    The Hadoop Distributed File System (HDFS) is a large data storage system which exhibits several features of a good distributed file system. In this paper we integrate Matlab Distributed Computing Server (MDCS) with HDFS to build a scalable, efficient platform for scientific computations. We use an FTP server on top of HDFS for data transfer from the Matlab system to HDFS. The motivation of using HDFS for storage with MDCS is to provide an efficient, fault-tolerant file system and also to utilize the resources efficiently by making each system serve as both data node for HDFS and worker for MDCS. We test the storage efficiency of HDFS and compare with normal file system for data transfer operations through MDCS. © 2012 IEEE.
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    Privacy and trust in cloud database using threshold-based secret sharing
    (2013) Dutta, R.; Annappa, B.
    In today's cloud computing scenario, privacy of data and trust on the service provider have become a major issue and concern. Achieving trust and preserving the privacy of data stored in third-party cloud databases has emerged as a key research area. To achieve this, several different techniques have been proposed based on cryptography, auditing by a third party, etc. Secret sharing schemes have also been considered to address these issues of trust and privacy in databases by various researchers. In this paper, we propose a technique of using a well-known threshold-based visual secret sharing scheme to address the issue of privacy and trust in cloud databases and database-as-a-service offerings. We consider data records with at least one prime attribute and propose an indexing technique for the secret shares of records in a large database based on some properties of the secret sharing technique. Our technique is aimed at minimizing storage overhead of secret shares as well as high speed upload and retrieval of data. We discuss the results obtained from our implementation. Our implementation using Hadoop Distributed File System (HDFS) with Matlab shows that this technique minimizes storage overhead due to secret shares and ensures high speed data upload and retrieval. © 2013 IEEE.