Cyber Graph-to-Text: AI automation for Threat Intelligence, made accessible to all

情报循环是收集、分析和传播情报以帮助决策者了解环境并做出适当决策的过程。然而，由于人类大脑在规模、速度和容量方面的限制，它无法在全球范围内进行必要的分析，以发现和跟踪网络威胁。由于每天都会产生大量关于网络威胁的信息，人类无法独自完成这个循环，我们需要一个替代解决方案。我们的人工智能将通过分析分析师在网络威胁情报（CTI）馈送中创建的数千条情报，自动识别、量化和预测网络威胁。通过自动提供CTI的首次分析，我们的人工智能将节省时间、金钱和执行手动CTI分析的专业分析师的精力；以及为更多没有专业情报培训或专业知识的通才安全分析师规避CTI分析的痛点，进一步在最终用户组织内分散负载。一个成功的项目将为英国plc节省数十亿英镑，通过确保更快有效地防御新的和正在出现的网络威胁，有助于使英国成为最安全的生活和在线商业场所的目标。

The intelligence cycle is the process of collecting, analysing, and disseminating intelligence to help decision makers understand their environment and make appropriate decisions. However, the human mind is not capable of performing the necessary analysis to find and track cyber-threats on a global scale due to its limitations in size, speed, and capacity. As humans are not able to complete this cycle on their own due to the sheer scale of information being generated about cyber threats every day, we need an alternative solution.Our AI will automatically identify, quantify, and predict cyber-threats by analysing thousands of pieces of intelligence created by analysts in cyber threat intelligence (CTI) feeds. By providing a first cut analysis of CTI automatically, our AI will save time, money, and effort from specialist analysts who perform manual CTI analysis; as well as circumvent the CTI analysis pain-point for more generalist security analysts who have no specialty intelligence training or expertise, further spreading the load within end-user organisations. A successful project will potentially save £billions for UK plc by ensuring faster effective defence from new and emerging cyber threats, contributing to the aim of making the UK the safest place to live and do business online.