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 DNA based service data security in cloud computing environment
Tác giả hoặc Nhóm tác giả: Amisha Patel; Zhongyan Ge; Indra Seher; Van Luong Vo
Nơi đăng: 2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA); Số: 10.1109/CITISIA53721.2021.9719943;Từ->đến trang: 21 -28;Năm: 2021
Lĩnh vực: Công nghệ thông tin; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
Cloud computing is the type of technology preferred to maintain computing power, computer resources, and majorly used to handle the cloud storage process. Also, it helps to manage the data security process during different applications. The data encryption, data classification, and feature extraction approaches are majorly considered for increasing the data security process. The main aim of the work is to review the DNA based cloud computing process for improving data security. The main purpose of this work is to review the current research article focus on the data security and computing process. Further, taxonomy is introduced that helps in the evaluation and analysis process. The secondary research approach is used during review work. Further, the deep learning with sequencing and modification process is reviewed in the work to manage the security and sequence analysis process. In addition, the block-chain-based random technique is reviewed to manage data detection and probability rate. The data optimization and data indexing process with block-chain is preferred to enhance data security and handle the feasibility, accuracy, and transfer time. Moreover, the OPNET model, Dynamic and static model approach, and data access algorithms are used together for maintaining the data mining security process. The IoT network topology and attributes based encryption process are reviewed in developed methods for maintaining data optimization and data security process. These approaches and factors are analyzed with the help of current research articles in order to review the state of the art in the developed method.
ABSTRACT
Cloud computing is the type of technology preferred to maintain computing power, computer resources, and majorly used to handle the cloud storage process. Also, it helps to manage the data security process during different applications. The data encryption, data classification, and feature extraction approaches are majorly considered for increasing the data security process. The main aim of the work is to review the DNA based cloud computing process for improving data security. The main purpose of this work is to review the current research article focus on the data security and computing process. Further, taxonomy is introduced that helps in the evaluation and analysis process. The secondary research approach is used during review work. Further, the deep learning with sequencing and modification process is reviewed in the work to manage the security and sequence analysis process. In addition, the block-chain-based random technique is reviewed to manage data detection and probability rate. The data optimization and data indexing process with block-chain is preferred to enhance data security and handle the feasibility, accuracy, and transfer time. Moreover, the OPNET model, Dynamic and static model approach, and data access algorithms are used together for maintaining the data mining security process. The IoT network topology and attributes based encryption process are reviewed in developed methods for maintaining data optimization and data security process. These approaches and factors are analyzed with the help of current research articles in order to review the state of the art in the developed method.
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