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首页> 外文会议>International Conference on Computing for Geospatial Research and Application >Dynamic Protection for Critical Health Care Systems Using Cisco CWS: Unleashing the Power of Big Data Analytics
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Dynamic Protection for Critical Health Care Systems Using Cisco CWS: Unleashing the Power of Big Data Analytics

机译：使用Cisco CWS的关键医疗系统的动态保护：释放大数据分析的力量

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Critical Care IT systems such as life support devices, vitals monitoring systems, information systems that provide point of care guidance to care teams are a key component of a lifesaving effort in Healthcare. The mega trends of mobility, social, cloud combined with wide spread increase and sophistication of malware, has created new challenges and the point in time detection methods at the hospitals are no longer effective and pose a big threat to the critical care systems. To maintain the availability and integrity of these critical care systems, new adaptive, learning security defense systems are required that not only learns from the traffic entering the hospital, but also proactively learns from the traffic worldwide. Cisco's Cloud web security (CWS) provides industry-leading security and control for the distributed enterprise by protecting users everywhere, anytime through Cisco worldwide threat intelligence, advanced threat defense capabilities, and roaming user protection. It leverages the big data to perform behavioral analysis, anomaly detection, evasion resistance, rapid Detection services using flow based, signature based, behavior based and full packet capture models to identify threats. This tech talk looks at how big Data Analytics is used in combination with other security capabilities to proactively identify threats and prevent wide spread damage to healthcare critical assets.
机译：重症监护IT系统（例如生命支持设备，生命监测系统，向护理团队提供护理点指导的信息系统）是医疗保健中救生工作的关键组成部分。移动性，社交性，云计算的巨大趋势，加上恶意软件的广泛传播和复杂性，带来了新的挑战，医院的时间点检测方法不再有效，并且对重症监护系统构成了巨大威胁。为了维持这些重症监护系统的可用性和完整性，需要新的适应性学习安全防御系统，该系统不仅要从进入医院的流量中学习，而且还要从全世界的流量中积极学习。思科的云网络安全（CWS）通过思科全球威胁情报，高级威胁防御功能和漫游用户保护，随时随地保护用户，从而为分布式企业提供行业领先的安全性和控制力。它利用大数据通过基于流，基于签名，基于行为和完整的数据包捕获模型来执行行为分析，异常检测，逃避抵抗，快速检测服务，以识别威胁。本技术讲座探讨如何将大型数据分析与其他安全功能结合使用，以主动识别威胁并防止对医疗保健关键资产的广泛破坏。

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