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

机译:实时大数据分析:安全问题和机器学习算法挑战

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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:凭借巨大的数据力量是责任!一个大数据倡议不仅要关注数据的卷,速度或各种各样,还要采用保护它的最佳方法。安全性通常是事后,但元素提供了正确的技术框架,以使您的深度可见性和多层安全性所需的任何大数据项目。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现安全控制,同时使用可操作的智能将鸟瞰在整个系统上,以阻止任何恶意活动,新兴威胁和漏洞。机器学习的进步(ML)为应用,技术和理论遇到的安全问题提供了新的挑战和解决方案。机器学习(ML)技术在安全问题中发现了广泛的应用和实现。许多ML技术,方法,算法,方法和工具被安全专家和研究人员广泛使用,以实现更好的结果和设计强大的系统。

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