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ANALYZING BIG, MIDSIZE, AND SMALL DATA FOR APPLICATION SECURITY

机译:分析大数据,中型数据和小型数据以确保应用程序安全

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摘要

Organizations collect huge amounts of security intelligence and yet analysts fail to anticipate many attacks leading to data breaches, denials of service, identity theft, fraudulent use of systems and data, and other nefarious activities. Analysts mostly learn of incidents from third parties, such as law enforcement and payment-card processing companies. Could it be that they do not have available the right level and mix of data? We describe how one might optimize the collection and analysis of security information and event management data, particularly as they apply to securing computer applications. It is argued that this optimization can be achieved by combining big, midsize, and small data and running them through appropriate analytical methods.
机译:组织收集了大量的安全情报,但分析人员未能预料到许多攻击会导致数据泄露,服务拒绝,身份盗用,欺诈性使用系统和数据以及其他恶意活动。分析师大多是从第三方(例如执法和支付卡处理公司)那里了解事件。可能是他们没有可用的正确级别和数据混合吗?我们描述了如何优化安全信息和事件管理数据的收集和分析,尤其是当它们应用于保护计算机应用程序时。有人认为,可以通过组合大,中,小数据并通过适当的分析方法运行它们来实现此优化。

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