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http://dx.doi.org/10.3837/tiis.2021.11.008

An IPSO-KELM based malicious behaviour detection and SHA256-RSA based secure data transmission in the cloud paradigm  

Ponnuviji, N.P. (Department of Computer Science and Engineering, R.M.D. Engineering College)
Prem, M. Vigilson (Department of Computer Science and Engineering, R.M.D. Engineering College)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.11, 2021 , pp. 4011-4027 More about this Journal
Abstract
Cloud Computing has emerged as an extensively used technology not only in the IT sector but almost in all sectors. As the nature of the cloud is distributed and dynamic, the jeopardies present in the current implementations of virtualization, numerous security threats and attacks have been reported. Considering the potent architecture and the system complexity, it is indispensable to adopt fundamentals. This paper proposes a secure authentication and data sharing scheme for providing security to the cloud data. An efficient IPSO-KELM is proposed for detecting the malicious behaviour of the user. Initially, the proposed method starts with the authentication phase of the data sender. After authentication, the sender sends the data to the cloud, and the IPSO-KELM identifies if the received data from the sender is an attacked one or normal data i.e. the algorithm identifies if the data is received from a malicious sender or authenticated sender. If the data received from the sender is identified to be normal data, then the data is securely shared with the data receiver using SHA256-RSA algorithm. The upshot of the proposed method are scrutinized by identifying the dissimilarities with the other existing techniques to confirm that the proposed IPSO-KELM and SHA256-RSA works well for malicious user detection and secure data sharing in the cloud.
Keywords
Cloud computing; Data security; Attack detection; Malicious user detection; Secure authentication; SHA256 hashing; Rivest Shamir Adleman (RSA) encryption; Kernel Extreme Learning Machine (KELM);
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