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首页> 外文期刊>Indian Journal of Science and Technology >Neural based Security Approach for Cloud Databases using Counter Propagation
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Neural based Security Approach for Cloud Databases using Counter Propagation

机译:使用反向传播的基于神经网络的云数据库安全方法

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Neural Network is an efficient implementing technique for cryptographic algorithms to provide security in cloud environment. Cloud Computing is an outsourced on-demand computing service, where Privacy preserving is very difficult to provide. Secured Data Sharing is important in cloud storage aspect. The proposed Neural Data Security Model ensures high data confidentiality and security in cloud database environment. This Model is a combination of , Sensitive Data Component (SDC) and Counter Propagation Neural Data Security Component (CPNDSC). The Sensitive data Component is implemented for storing the fragmented sensitive data. In Neural Data Security Component the Neural cryptographic algorithm is used to encrypt the sensitive data to enhance the confidentiality level by using Counter Propagation Neural Network.This reasearch is carried on cloud databases and artificial Neural Network that achieves high data security in cloud environment.
机译:神经网络是一种有效的加密算法实施技术,可在云环境中提供安全性。云计算是一项外包的按需计算服务,其中很难提供隐私保护。安全数据共享在云存储方面非常重要。所提出的神经数据安全模型可确保云数据库环境中的高度数据机密性和安全性。该模型是敏感数据组件(SDC)和反向传播神经数据安全组件(CPNDSC)的组合。敏感数据组件实现用于存储碎片敏感数据。在神经数据安全组件中,使用神经密码算法通过使用反向传播神经网络对敏感数据进行加密以提高机密性水平。该研究是在云数据库和人工神经网络上进行的,从而在云环境中实现了高数据安全性。

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