A novel double keys adapted elliptic curve cryptography and log normalized Gaussian sigmoid adaptive neuro‐fuzzy interference system based secure resource allocation system in decentralized cloud storage. Issue 4 (14th December 2022)

• Record Type: Journal Article
• Authors: Karuppasamy, Lakshmanan; Vasudevan, Venkatraman
• Is Part Of: Expert systems. Volume 40:Issue 4(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-14
• Subjects: adaptive neuro‐fuzzy interference system -- and elliptic curve cryptography -- cosine similarity -- data security -- decentralized cloud storage -- Gaussian sigmoid activation -- resource allocation; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.13206
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: Cloud computing has emerged as a promising platform that grants users direct yet shared access to computing resources and services without worrying about the internal complex infrastructure. However, secure data storage and data retrieval is the basic characteristics. Therefore, this paper proposes a novel double keys adapted elliptic curve cryptography (DKECC) and log normalized Gaussian sigmoid adaptive neuro‐fuzzy interference system (LGS‐ANFIS) based secure resource allocation system in decentralized cloud storage. Initially, the input data undergoes data fragmentation. After that, encryption is carried out using DKECC algorithm. Next, hash code generation using Pearson hash function is done. Then, resource availability is estimated via logistic sine chaotic mapping indulged rock hyraxes swarm optimization technique. Afterwards, data is checked for deduplication. Finally, resource allocation through LGS‐ANFIS takes place. The experimental outcomes demonstrated better results compared to baseline techniques. The modelling process showed that the suggested safe resource allocation model achieves the total security level of 96.27% while also having shorter reaction times (3018 ms), greater throughputs (1258), reduced load balancing (0.355874), and reduced latency (4372 ms).