LEADS-Engine: Linguistically Enabled Analytic Dark Search Engine

**项目愿景**英国国家欺诈和网络犯罪仪表板(NFB)显示，到2021年为止，组织受到了57304起与欺诈相关的网络犯罪的影响，损失达6.374亿英镑。随着网络攻击转向远程/家庭工作(Mimecast.com)，网络攻击上升了%。暗网为非法活动/技术的组织、实施和传播提供了一种手段，超过50%的Tor(最受欢迎的暗网网络)网站致力于非法活动(Terbium实验室)。虽然有多种暗网监控工具/服务，但都缺乏基于行为模式自动识别威胁的能力，目前需要使用法医语言学等技术进行广泛的手动分析。仅由阿斯顿法医语言学研究所(AIFL)等专业学术研究人员提供。在采用威胁情报安全解决方案的需求(Hiscox，2019年)的推动下，全球威胁情报市场预计到2025年将达到161亿美元(市场和市场)。**创新**法医路径有限公司(FPL)，一家总部位于英国的中小企业，已经开发了黑暗搜索引擎(DSE)，这是Tor.洋葱暗网的自动爬虫/爬行器。这个项目，语言启用的分析性黑暗搜索引擎(Leads-Engine)，将开发用于检测和预测网络犯罪/欺诈的创新技术，为DSE最终用户提供可用于制定保护措施/系统的可行情报。我们将与AIFL在Leads-Engine合作，通过提供可行情报和实现快速识别新威胁，实现快速识别新威胁，提供风险评估工具，并添加到不断发展的在线欺诈策略和行为数据库中，从而超越最先进的监测/警报。

**Vision for the Project**The UK National Fraud and Cyber Crime Dashboard (NFB) shows that, to-date in 2021, organisations have been impacted by 57,304 fraud-related cybercrimes, costing £637.4m. There has been a 64% rise in cyber-attacks with the shift to remote/home working (mimecast.com).The Dark Web provides a means for the organisation, conduct, and spread of illicit activity/techniques, with over 50% of Tor (the most popular Dark Web network) websites dedicated to illegal activity (Terbium Labs).While there are multiple dark web monitoring tools/services, all lack the ability to automatically identify threats based on behavioural patterns, which currently requires extensive manual analysis using techniques like Forensic Linguistics, only available from specialist academic researchers such as the Aston Institute for Forensic Linguistics (AIFL).The global threat intelligence market is projected to reach $16.1 billion by 2025 (MarketsAndMarkets.com), driven by the need to adopt threat intelligence security solutions (Hiscox, 2019).**Innovation**Forensic Pathways Limited (FPL), a UK-based SME, has developed Dark Search Engine (DSE), an automated crawler/scraper of the Tor .onion Dark Web. This project, Linguistically Enabled Analytic Dark Search Engine (LEADS-Engine), will develop innovative techniques for the detection and prediction of cybercrime/fraud, providing DSE end-users with actionable intelligence they can use to develop their protection measures/systems.We will team with AIFL in LEADS-Engine to go beyond the monitoring/alerting state-of-the-art by providing actionable intelligence and enabling the rapid identification of new threats, feeding into risk assessment tools and adding to a continually developing database of online fraud strategies and behaviours.