LEADS-Engine: Linguistically Enabled Analytic Dark Search Engine
Lead Participant:
FORENSIC PATHWAYS LIMITED
Abstract
**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.
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.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| FORENSIC PATHWAYS LIMITED | £220,284 | £ 154,199 |
Participant |
||
| ASTON UNIVERSITY | £91,366 | £ 91,366 |
| INNOVATE UK |
People |
ORCID iD |
| Deborah Leary (Project Manager) |