Big Data-driven Approach for the Next Generation User Authentication

数字数据的显著增长正在改变对未知的防御将发生的内容和方式。大数据是一个技术术语，用来表示从许多来源产生的数字数据的大规模增长。组织已经将注意力转向部署大数据分析，以获得有价值的见解，从而在受保护和安全的环境中使其业务受益。因此，网络安全协议正在被重新设计，以管理大数据的特征，最终将带来数据增长的真正好处。******与传统观点相反，研究人员关注于识别用户身份以保护基于大数据的环境，我的观点是矛盾的。我相信大数据本身将成为下一代用户认证的燃料。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的特征的真正理解，从而根据用户的实时行为做出认证决策。******拟议的研究计划包括三个短期目标，旨在调查大数据驱动的身份验证方法的发展，从而为寻求更强大的身份验证、成本效益和方便的用户体验的组织提供新的用例。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)基于大数据分析的实时人类动态测量工具******研究大规模数据处理引擎（如Spark和Hadoop）的部署，以开发新的基于数据安全的分析（DSA）工具。用于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，开发大数据驱动认证模型（BDA）。******2)大数据驱动的认证即服务模型******设计和开发基于saas的认证（AUTHaaS）模型。一种由DSA、BDA和JitHDA技术支持的大数据驱动身份验证的新方法，与上面的第一个组件一起启动和发布。这些服务应符合加拿大的数据隐私立法。******3)促进多个大数据驱动的认证服务提供商协作和互操作性的集成框架******设计和开发一个新的框架（iAUTH），以提供在多个认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性混乱。本文将使用“Syverson and Van Oorschot”SVO的形式化方法分析来验证该框架的正确性。

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.