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Comparative Analysis of a Systematic Coherent Encryption Scheme for Large-Scale Data Management Using Cryptographic Encryption Technique

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 105))

Abstract

In today’s world of technology, Data has been playing an imperative role in many different technical areas. Data confidentiality, integrity and data security over Internet from different media and applications has greater challenges tasks. Data generation from multimedia and IoT data is the biggest Big Data in Internet now. When sensitive and confidential data are counterfeit by attacks this lead to serious countermeasures to security and privacy. Data Encryption is the mechanism to forestall this issue. At present, many encryption techniques are used for multimedia and IoT but when there is massive data are developed it incur more computational challenge. This paper design and propose new coherent encryption algorithm which holds issue of IoT and multimedia big data. The proposed system can cause a strong cryptographic effect without hold much memory and easy performance analysis. Handling huge data with the help GPU is included in the proposed system to enhance the data processing more efficiently. The proposed algorithm is compared with other symmetric cryptographic algorithms like AES, DES, 3-DES, RC6 and MARS based on architecture, flexibility, scalability, security level and also based on computational Running time, Throughput for both encryption and decryption process. Avalanche effect is also calculated for proposed system with 54.2%. The proposed framework holds to secure the multimedia against real-time attacks.

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Correspondence to A. Stephen Dass .

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Stephen Dass, A., Prabhu, J. (2019). Comparative Analysis of a Systematic Coherent Encryption Scheme for Large-Scale Data Management Using Cryptographic Encryption Technique. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 105. Springer, Singapore. https://doi.org/10.1007/978-981-13-1927-3_46

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  • DOI: https://doi.org/10.1007/978-981-13-1927-3_46

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1926-6

  • Online ISBN: 978-981-13-1927-3

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