I. Mettildha Mary^1,*, K. Karuppasamy²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2667-2685, 2023, DOI:10.32604/csse.2023.031114

Abstract CC’s (Cloud Computing) networks are distributed and dynamic as signals appear/disappear or lose significance. MLTs (Machine learning Techniques) train datasets which sometime are inadequate in terms of sample for inferring information. A dynamic strategy, DevMLOps (Development Machine Learning Operations) used in automatic selections and tunings of MLTs result in significant performance differences. But, the scheme has many disadvantages including continuity in training, more samples and training time in feature selections and increased classification execution times. RFEs (Recursive Feature Eliminations) are computationally very expensive in its operations as it traverses through each feature without considering correlations between them. This problem can… More >

Abdul Saboor^1,*, Mohd Fadzil Hassan², Rehan Akbar¹, Erwin Susanto³, Syed Nasir Mehmood Shah⁴, Muhammad Aadil Siddiqui⁵, Saeed Ahmed Magsi⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2223-2239, 2022, DOI:10.32604/cmc.2022.028382

Abstract Cloud computing has gained significant use over the last decade due to its several benefits, including cost savings associated with setup, deployments, delivery, physical resource sharing across virtual machines, and availability of on-demand cloud services. However, in addition to usual threats in almost every computing environment, cloud computing has also introduced a set of new threats as consumers share physical resources due to the physical co-location paradigm. Furthermore, since there are a growing number of attacks directed at cloud environments (including dictionary attacks, replay code attacks, denial of service attacks, rootkit attacks, code injection attacks, etc.), customers require additional assurances… More >