Linear Elliptical Curve Digital Signature (LECDS) With Blockchain Approach for Enhanced Security on Cloud Server

【Author】 Sowmiya, B.; Poovammal, E.; Ramana, Kadiyala; Singh, Saurabh; Yoon, Byungun

【Source】IEEE ACCESS

【影响因子】3.476

【Abstract】Cloud computing is a continuously evolving technology that can enhance agility, availability, collaboration and scalability of data. Blockchain has a secure, immutable ledger which maintains all the transactions along with the timestamp. The blockchain framework and cloud computing technology jointly provides different ways of computational cost reduction. The existing methods help to identify the anonymous documents which are given in the form of requests from the cloud server. If the anonymized document requests are from the authorized users, then cloud provides better security and hence documents are not available for unauthorized users. But the main issue is access rights available for authorized users on sensitive data of the owner. To maintain the privacy the sensitive data are hidden using cryptographic techniques even for authorized users. The method adopted is Linear Elliptical Curve Digital Signature (LECDS) with Hyperledger blockchain, to prevent private data loss. The Linear regression method is used to classify the user information into two classes namely sensitive and non-sensitive. The non-sensitive data is encrypted using RSA and sensitive data is encrypted using LECC method. Modified Spider optimization search Algorithm (MSOA) is used to verify the integrity of outsourced data and search user query information in a cloud server. The hyper ledger blockchain verifies the user policy to create a private network through which the user communicates the cloud. In the analysis of the proposed method, the results are evaluated using various performance metrics such as security, throughput, classification accuracy and error rate.

【Keywords】Blockchains; Distributed ledger; Cloud computing; Security; Cryptography; Servers; Fabrics; Hyperledger blockchain; modified spider search; cloud computing

【发表时间】2021

【收录时间】2022-01-02

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