Memory Based Hybrid Dragonfly Optimization for Multiple Key Generation using Cloud Computing
C. Kaleeswari1, K. Kuppusamy2
1C. Kaleeswari*, Dept. of Computational Logisticshis, Alagappa University, Karaikudi, India.
2K. Kuppusamy, Dept. of Computational Logistics, Alagappa University, Karaikudi, India. 

Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4442-4451 | Volume-8 Issue-5, January 2020. | Retrieval Number: E7042018520/2020©BEIESP | DOI: 10.35940/ijrte.E7042.018520

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Abstract: Cloud Computing, as a new technology with enormous computing services, evolved in recent era. It is a most promising computing that gives services on – demand. The Cloud services becomes a noticeable paradigm, by it notable features like, shared pool of resources, Shared infrastructure, dynamic provisioning, network access, handled assessing forward with gassed-up, gullibility, resilience and adoptable. Likewise, it has influence, Cloud Computing has some issues like security of data transferred via the Cloud, availability of resources and its authenticity, remains as a major task of attention. A Novel Optimized Encrytion-As-A-Service is presented in this paper, with multiple keys generation methodology. The three various Key generation includes, Pseudo Random Number Generator (PRNG), Sub-optimal keys are generated from hybridization of Improved Cipher Block Chaining (ICBC) encryption algorithm and final key is from Memory based Hybrid Dragonfly Optimization Algorithm (MHDA). In turn, MHDA is the combination of Dragonfly Optimization Algorithm (DA) and Particle Swarm Optimization Algorithm (PSO) for generating the innovative key for encryption of data. MHDA gives the better performance analysis compared with DA and PSO optimization approaches. The milestone of this optimized hybridization algorithm is to reduce the time complexity and increase the quality of encryption of the data. The experimental analysis is done for Text, image data and performance metrics are evaluated for the proposed research work. Different parameter that explores the main capacity and strength of the algorithm is examined.
Keywords: Cloud Computing, MHDA, RGB Color Image, Authentication, ICBC Encryption, Decryption.
Scope of the Article: Cloud Computing,