NERD：用于风险数据流判定的神经网络
NERD: Neural Network for Edict of Risky Data Streams
摘要：
网络事件可能有各种各样的原因，从简单的连接丢失到持续的攻击。一旦发现潜在的网络安全事件和系统故障，决定如何继续通常是复杂的。特别是，如果真正的原因是不能直接详细确定。因此，我们开发了网络事件处理支持系统的概念。所开发的系统是丰富的信息多个来源，如入侵检测系统和监测工具。它使用超过20个关键属性（如同步包比率）来识别潜在的安全事件，并将数据分类为不同的优先级类别。之后，该系统使用人工智能来支持进一步的决策过程，并生成相应的报告向董事会汇报。在此基础上，对故障原因和排除措施提出了相应的建议。来自用户的关于问题解决方案的反馈通过使用标记的流数据作为学习过程的输入而被包括到未来的决策中。原型表明，决策可以持续改善和网络事件处理过程变得更加有效。
英文摘要：
Cyber incidents can have a wide range of cause from a simple connection loss to an insistent attack. Once a potential cyber security incidents and system failures have been identified, deciding how to proceed is often complex. Especially, if the real cause is not directly in detail determinable. Therefore, we developed the concept of a Cyber Incident Handling Support System. The developed system is enriched with information by multiple sources such as intrusion detection systems and monitoring tools. It uses over twenty key attributes like sync-package ratio to identify potential security incidents and to classify the data into different priority categories. Afterwards, the system uses artificial intelligence to support the further decision-making process and to generate corresponding reports to brief the Board of Directors. Originating from this information, appropriate and detailed suggestions are made regarding the causes and troubleshooting measures. Feedback from users regarding the problem solutions are included into future decision-making by using labelled flow data as input for the learning process. The prototype shows that the decision making can be sustainably improved and the Cyber Incident Handling process becomes much more effective.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
