提高 SPARK 集群的数据安全性:基于符号的新型认证方法

J.Balaraju, C.Dastagiraiah, P.Ravinder Rao, T.Srikanth, K.Jyothi Goud, V.Subramanyam
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引用次数: 0

摘要

用户身份验证是指在允许个人访问联网设备、在线服务或任何其他有价值的资源之前对其身份进行确认的过程。用户身份验证的重要性在于,它能够通过限制授权个人或批准流程的访问,为企业的数据、应用程序和网络提供保护。本研究采用了广泛使用的 Apache Spark 技术来存储和分析海量数据,并引入了独特的身份验证框架。动态符号选择认证为传统的字母数字密码以及生物识别和面部认证提供了一种有前途的替代方法。这种身份验证方法已在高度分布式的 Apache Spark 集群中进行了全面测试。实施过程中以各种方式利用了 SHA512 加密技术,并将结果与现有的身份验证和机器学习算法进行了比较。该身份验证方案与由 10 个节点组成的强大 Apache Spark 分布式系统相结合,取得了卓越的成果。
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Enhancing Data Security in SPARK Cluster: A Novel Symbol-based Authentication Approach
User authentication is the process of confirming an individual's identity prior to granting them access to a connected device, an online service, or any other valuable resource. Its importance lies in its capability to protect data, applications, and networks for organizations by restricting access to authorized individuals or approved processes. In this study, the widely used Apache Spark technology was employed for storing and analyzing vast amounts of data, and a unique authentication framework was introduced. A dynamic symbol selection authentication offers a promising alternative to traditional alphanumeric passwords, as well as biometric and facial authentications. This authentication method has been thoroughly tested in the highly distributed Apache Spark cluster. The implementation utilizes SHA512 cryptography in various ways and compares the results with existing authentication and machine learning algorithms. The authentication scheme, combined with the powerful Apache Spark distributed system consisting of 10 nodes, yielded exceptional outcomes.
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