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Real time BIG data analytic: Security concern and challenges with Machine Learning algorithm

机译:实时BIG数据分析:机器学习算法带来的安全问题和挑战

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摘要

With great power of data comes great responsibility! A big data initiative should not only focus on the volume, velocity or variety of the data, but also on the best way to protect it. Security is usually an afterthought, but Elemental provides the right technology framework to get you the deep visibility and multilayer security any big data project requires. Multilevel protection of your data processing nodes means implementing security controls at the application, operating system and network level while keeping a bird's eye on the entire system using actionable intelligence to deter any malicious activity, emerging threats and vulnerabilities. Advances in Machine Learning (ML) provide new challenges and solutions to the security problems encountered in applications, technologies and theories. Machine Learning (ML) techniques have found widespread applications and implementations in security issues. Many ML techniques, approaches, algorithms, methods and tools are extensively used by security experts and researchers to achieve better results and to design robust systems.
机译:强大的数据带来巨大的责任!大数据计划不仅应关注数据的数量,速度或种类,还应关注保护数据的最佳方法。安全通常是事后才想到的,但是Elemental提供了正确的技术框架,可为您提供任何大数据项目所需的深入可见性和多层安全性。数据处理节点的多级保护意味着在应用程序,操作系统和网络级别实施安全控制,同时使用可操作的情报来阻止整个恶意活动,新出现的威胁和漏洞,从而对整个系统保持警惕。机器学习(ML)的进步为应用程序,技术和理论中遇到的安全问题提出了新的挑战和解决方案。机器学习(ML)技术已在安全问题中找到了广泛的应用和实现。安全专家和研究人员广泛使用许多机器学习技术,方法,算法,方法和工具来获得更好的结果并设计健壮的系统。

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