Abdulbaqi Khashea A. Al-Hadeethi1 and Ezzeddine Zagrouba2, 1LIMTIC, LR16ES06 Research Laboratory, Higher Institute of Computer Science el Manar, Tunis "ISI" Tunis El-Manar University , Tunis , Tunisia, 2LIMTIC, LR16ES06 Research Laboratory, Higher Institute of Computer Science el Manar, Tunis "ISI" Tunis El-Manar University , Tunis , Tunisia
Trust in authority is foundational to the successful adoption and utilization of cloud data-based information in data mining technology. Organizations entrust their sensitive data to cloud service providers, relying on them to ensure security. The technique include in this methods are Data collection and pre-processing, Feature extraction, Feature selection, Classification, Trust authentication, Encryption and decryption. To the raw data undergoes pre-processing steps include, Dimensionality reduction, feature encoding, and normalization techniques are used .the Hybrid Gray Level Co-occurrence Matrix Fast Fourier Transform (HGLCM-FFT) technique is used Feature extraction. The filter-based techniques such as symmetric uncertainty, IG, gain ratio, and CS are for used the Feature selection. The Hierarchical Gradient Boosted Isolation Forest (HGB-IF) algorithm is used for the classification .Trust authentication is used for security framework that functions across distributed cloud settings is provided a Distributed Adaptive Trust-Based Authentication (DAT-BA). By employing Particle Swarm Optimized Symmetrical Blowfish (PSOSB) algorithm is used for Encryption and decryption. The suggested work is implemented using OS Python – 3.9.6 , The performance of the suggested model are Attack Detection Rate ,False alarm rate, True positive rate, Network usage, CPU usage, Encryption time, Decryption time, Throughput.
Data Mining, Cloud computing, the Hybrid Gray Level Co-occurrence Matrix Fast Fourier Transform (HGLCM-FFT) algorithm, The Hierarchical Gradient Boosted Isolation Forest (HGB-IF) algorithm, Particle Swarm Optimized Symmetrical Blowfish (PSOSB) algorithm, Encryption time.
