In this paper, we present an operational system for cyber threat intelligence gathering from various social platforms on the Internet particularly sites on the darknet and deepnet. We focus our attention to collecting information from hacker forum discussions and marketplaces offering products and services focusing on malicious hacking. We have developed an operational system for obtaining information from these sites for the purposes of identifying emerging cyber threats. Currently, this system collects on average 305 high-quality cyber threat warnings each week. These threat warnings include information on newly developed malware and exploits that have not yet been deployed in a cyber-attack. This provides a significant service to cyber-defenders. The system is significantly augmented through the use of various data mining and machine learning techniques. With the use of machine learning models, we are able to recall 92% of products in marketplaces and 80% of discussions on forums relating to malicious hacking with high precision. We perform preliminary analysis on the data collected, demonstrating its application to aid a security expert for better threat analysis.
翻译:在本文中,我们展示了从互联网上各种社会平台收集网络威胁情报的操作系统,特别是黑网和深网网站;我们集中关注从黑客论坛讨论和市场收集信息,提供以恶意黑客为重点的产品和服务;我们开发了从这些网站获取信息的操作系统,以查明新出现的网络威胁;目前,该系统平均每星期平均收集305次高质量的网络威胁警告;这些威胁警告包括新开发的恶意软件和尚未在网络攻击中部署的利用的信息;这为网络破坏者提供了重要服务;通过使用各种数据挖掘和机器学习技术大大扩展了该系统;通过使用机器学习模型,我们可以回顾市场92%的产品和80%的关于恶意黑客论坛的讨论;我们对所收集的数据进行了初步分析,展示了它用于帮助安全专家进行更好的威胁分析的应用。