Big Data-driven Approach for the Next Generation User Authentication

数字数据的显著增长正在改变针对未知事物的防御内容和方式。大数据是今天使用的一个技术术语，用来表示从许多来源创建的数字数据的大规模增长。组织已将注意力转向大数据分析的部署，以获得有价值的见解，使其企业在受保护和安全的环境中受益。因此，网络安全协议正在重新设计，以管理大数据的特性，这最终将带来这种数据增长的真正好处。 与研究人员专注于识别用户身份以保护基于大数据的环境的传统观点相反，我有一个相互矛盾的观点。我相信，大数据本身将是下一代用户身份验证的燃料。换句话说，该研究计划的目标是开发一种新的信息安全方法，利用大数据分析来提供对人们特征的真实了解，根据这些特征，将根据用户的即时行为做出身份验证决定。 拟议的研究计划涉及三个短期目标，旨在调查大数据驱动的身份验证方法的发展，这反过来将为寻求更强大的身份验证、经济高效和便捷的用户体验的组织提供新的使用案例。这三个目标将考虑分析、设计和实现的所有方面，以交付以下组件。 1)基于大数据分析的工具，用于测量实时人体动力学 研究Spark和Hadoop等大型数据处理引擎的部署，以开发新的基于数据安全的分析(DSA)工具。构建认知分析方法的设计方法，以区分具有安全/识别潜力的数据。最后，开发大数据驱动的身份验证模型(BDA)。 2)大数据驱动的身份认证即服务模型 设计并开发了基于SaaS的认证(AUTHaaS)模型。由DSA、BDA和JitHDA技术支持的大数据驱动的身份验证新方法，随上述第一个组件一起启动和提供。这些服务应符合加拿大的数据隐私立法。 3)集成框架，促进多个大数据驱动的身份认证服务提供商之间的协作和互操作 设计和开发新的框架(IAUTH)，以提供在多个身份验证服务提供商之间利用DSA、BDA和JitHDA技术所需的统一接口。这促进了简单性，并避免了任何安全混乱。该框架的正确性将使用形式化方法分析“Syverson and Van Oorscht”SVO来验证。

The remarkable growth in digital data is changing what and how the defense against the unknown will take place. Big data is a technical term used today to represent this massive growth of digital data that's being created from many sources. Organizations have turned their attentions to the deployment of Big Data analytics to gain valuable insights that benefit their businesses within protected and secure environments. Hence, network security protocols are being re-designed to manage the characteristics of Big Data which will eventually deliver the real benefits of this data growth. Contrary to the traditional perspective, in which researchers focus on identifying users' identity to protect Big Data-based environments, I have a contradictory perspective. I believe that Big Data itself will be the fuel for the next generation user authentication. In other words, the goal of this research program is to develop a new approach to information security that leverages Big Data analytics to provide true understanding of people's traits by which authentication decisions would be taken based on what users do on moment-to-moment basis. The proposed research program involves three short-term objectives that aim to investigate the development of the Big Data-driven authentication approach that in turn will provide new use cases for organizations who are looking for stronger authentication, cost-effective, and a convenient user experience. These three objectives will consider all aspects of the analysis, the design, and the implementation to deliver the following components. 1) Big Data analytics-based tools for measuring real-time human dynamics Investigate the deployment of large-scale data processing engines, such as Spark and Hadoop, to develop new Data Security-based Analytics (DSA) tool. Design methodology for building cognitive analytics methods to distinguish the data that has security/identification potentials. Finally, develop the Big Data-driven authentication model (BDA). 2) Big Data-driven Authentication as a Service Model Design and develop SaaS-based authentication (AUTHaaS ) model. A new approach for Big Data driven authentication that is powered by DSA, BDA, and JitHDA technologies initiated and shipped with the first component above. The services should be compliance with the data privacy legislation of Canada. 3) An integration framework to facilitate the collaboration and interoperability of multiple Big Data-driven authentication service providers Design and develop a new framework (iAUTH) to provide a unified interface necessary to leverage the DSA, BDA, and JitHDA technologies among multiple authentication service providers. This promotes simplicity and avoids any security chaos. The correctness of this framework will be verified using the formal method analysis “Syverson and Van Oorschot” SVO.