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Internet of Things Big Data Security in Cloud via Stream Cipher and Clustering Model

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Abstract

Big Data in IoT and Cloud Computing are two important developments over the years, enabling companies to provide efficient and effective IT services. To ensure the security of the information being processed, the information is usually stored within a year in a secure database. However, Encrypted Data Cloud introduces new duplication problems, which are important for storing large data. The proposed methodology consists of three segments that are Mapreduce framework, security, and authentication. Initially, the input dataset is mapped into multiple groups to minimize the volume of big data to maintain a strategic distance from scalability issues. To enhance the performance of SCA, the key values are optimally selected with the help of orthogonal learning particle swarm optimization (OLPSO) algorithm is utilized. After encryption process, the data are stored in cloud. In authentication phase, attribute-based access control mechanism is utilized. The proposed methodology performance is analyzed in terms of different metrics and performance is compared with different algorithms.

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Authors and Affiliations

  1. Research scholar, Department of Computer Science, S. T. Hindu College Research center, Affiliated to Manonmaniam Sundaranar University, Tirunelveli, Vinayagar Nagar, India

    K. S. Saraswathy

  2. Department of Computer Science, South Travancore Hindu College, Nagercoil, India

    S. S. Sujatha

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  1. K. S. Saraswathy
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Saraswathy, K.S., Sujatha, S.S. Internet of Things Big Data Security in Cloud via Stream Cipher and Clustering Model. Wireless Pers Commun 123, 3483–3496 (2022). https://doi.org/10.1007/s11277-021-09299-x

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