HOPLITE Threat Detection and Intelligence Sharing

ongoing

Real-time data analysis offers numerous benefits for public safety, enhancing the ability of law enforcement and emergency services to respond effectively and proactively to various threats and incidents. These include immediate threat detection, enhanced situational awareness, proactive policing, efficient resource allocation and improved emergency response strategies. The HOPLITE project will seek to improve law enforcement’s capacity to gather and analyse open and closed source data, to enhance public safety through intelligence-led response strategies. The goal will be to collect and correlate data and report threats in real-time by processing data sources including, but not limited to, instant messaging, social media feeds, video streams, and open and closed intelligence feeds. Building on existing tools for threat intelligence sharing and web scraping, HOPLITE will combat data overload by filtering and prioritising key data to the analyst through automated analysis and threat classification techniques. This will be driven by AI-based solutions for processing multi-modal and heterogeneous data, e.g., text, video, and audio. The results will be presented to the analyst in near real-time when the threat level is deemed to have exceeded the pre-defined threshold. Once notified, the analyst can review the intelligence presented and verify the results, adjusting the threat level accordingly and choosing whether to publish (share) the results. HOPLITE will utilise outputs from previously funded EU projects and others which are also freely available to law enforcement agencies (LEAs) and judicial authorities (JAs). These include, but are not limited to, MISP, AIL, INSPECTr and FREETOOL. These technologies will be integrated to provide a deployable solution for LEAs/JAs by the end of the project. HOPLITE will also draw on the experience of its consortium partners to develop training material and promote the project to relevant stakeholders.