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Security Aware Data Transaction Using Optimized Blowfish Algorithm in Cloud Environment

机译:安全意识数据事务在云环境中使用优化的河豚算法

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摘要

Cloud computing has become a growing technique due to its on-demand service and scalable features. Most of the applications of the cloud today are in data storage. Data protection and privacy have thus become a major concern. There are huge risks of storing transaction data on third-party hosts. Service providers need to make right investments in proving and ensuring appropriate security over time. Malicious users can exploit weak spots in the data protection model to increase unauthorized access to data. To overcome the problem, in this paper, security-aware data transaction on the cloud using the blowfish algorithm (BA) is proposed. To improve the security of the system, initially, the proposed system verifies the authentication of the user. After the authentication process, the uploaded data are initially split using a pattern-matching algorithm. Then, the separated data are encrypted with the help of BA. Finally, the encrypted data are stored in the cloud at an optimal location. This method is more secure as the data are column-separated and optimized in the cloud, so it is difficult to attack. This method is highly guaranteed because the user cannot recover the document without authentication checking. The performance of the proposed approach is analyzed in terms of different metrics, namely, memory, encryption and decryption time. The experimental results clearly say that the proposed method took minimum encryption time compared with the existing approach.
机译:由于其按需服务和可扩展功能,云计算已成为一种不断增长的技术。今天云的大多数应用都在数据存储中。因此,数据保护和隐私成为一个主要问题。在第三方主机上存储交易数据存在巨大风险。服务提供商需要在证明和确保随时间的适当安全方面进行正确的投资。恶意用户可以利用数据保护模型中的弱点,以增加对数据的未经授权访问。为了克服这个问题,提出了使用河豚算法(BA)的云上的安全感知数据事务。为了提高系统的安全性,最初,所提出的系统验证了用户的身份验证。在认证过程之后,上载的数据最初使用模式匹配算法拆分。然后,在BA的帮助下,分离的数据被加密。最后,加密数据在最佳位置存储在云中。这种方法更安全,因为数据在云中分开并优化,因此难以攻击。这种方法非常保证,因为用户无法在没有身份验证检查的情况下恢复文档。根据不同的指标,即内存,加密和解密时间,分析所提出的方法的性能。实验结果清楚地说,与现有方法相比,该方法采用了最小的加密时间。

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