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Panel Emerging Trends around Big Data Analytics and Security

机译:小组围绕大数据分析和安全的新兴趋势

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This panel will discuss the interplay between key emerging security trends centered around big data analytics and security. With the explosion of big data and advent of cloud computing, data analytics has not only become prevalent but also a critical business need. Internet applications today consume vast amounts of data collected from heterogeneous big data repositories and provide meaningful insights from it. These include applications for business forecasting, investment and finance, healthcare and well-being, science and hi-tech, to name a few. Security and operational intelligence is one of the critical areas where big data analytics is expected to play a crucial role. Security analytics in a big data environment presents a unique set of challenges, not properly addressed by the existing security incident and event monitoring (or SIEM) systems that typically work with a limited set of traditional data sources (firewall, IDS, etc.) in an enterprise network. A big data environment presents both a great opportunity and a challenge due to the explosion and heterogeneity of the potential data sources that extend the boundary of analytics to social networks, real time streams and other forms of highly contextual data that is characterized by high volume and speed. In addition to meeting infrastructure challenges, there remain additional unaddressed issues, including but not limited to development of self-evolving threat ontologies, integrated network and application layer analytics, and detection of "low and slow" attacks. At the same time, security analytics requires a high degree of data assurance, where assurance implies that the data be trustworthy as well as managed in a privacy preserving manner. Our panelists represent individuals from industry, academia, and government who are at the forefront of big data security analytics. They will provide insights into these unique challenges, survey the emerging trends, and lay out a vision for future.
机译:本面板将讨论以大数据分析和安全为中心的关键新兴安全趋势之间的相互作用。随着云计算的大数据和出现的爆炸,数据分析不仅变得普遍,而且还需要一个关键的业务需求。今天的Internet应用程序消耗了从异构大数据存储库中收集的大量数据,并从中提供有意义的见解。这些包括商业预测,投资和金融,医疗保健和福祉,科学和高科技的申请,为少数人名。安全性和操作智能是预计大数据分析的关键领域之一就会发挥至关重要的作用。大数据环境中的安全分析呈现出一系列独特的挑战,而不是通过通常使用有限的传统数据源(防火墙,ID等)的现有安全事件和事件监测(或暹粒)系统正确解决企业网络。由于潜在数据源的爆炸和异质性,潜在数据源的爆炸和异质性呈现出巨大的机会和挑战,这些源将分析边界扩展到社交网络,实时流和其他形式的高度上下文数据,这些数据的高卷和速度。除了满足基础设施挑战之外,还仍有额外的未解决问题,包括但不限于开发自我不断发展的威胁本体,集成网络和应用层分析,以及检测“低慢速”攻击。与此同时,安全分析需要高度的数据保证,保证暗示数据是值得信赖的,并以隐私保存方式管理。我们的小组成员代表了来自大数据安全分析的最前沿的行业,学术界和政府的个人。他们将向这些独特的挑战提供见解,调查新兴趋势,并为未来展示了愿景。

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