Deploying Semantic Web Technologies for Information Fusion of Terrorism-related Content and Threat Detection on the Web

Abstract

The Web and social media nowadays play an increasingly significant role in spreading terrorism-related propaganda and content. In order to deploy counterterrorism measures, authorities rely on automated systems for analysing text, multimedia, and social media content on the Web. However, since each of these systems is an isolated solution, investigators often face the challenge of having to cope with a diverse array of heterogeneous sources and formats that generate vast volumes of data. Semantic Web technologies can alleviate this problem by delivering a toolset of mechanisms for knowledge representation, information fusion, semantic search, and sophisticated analyses of terrorist networks and spatiotemporal information. In the Semantic Web environment, ontologies play a key role by offering a shared, uniform model for semantically integrating information from multimodal heterogeneous sources. An additional benefit is that ontologies can be augmented with powerful tools for semantic enrichment and reasoning. This paper presents such a unified semantic infrastructure for information fusion of terrorism-related content and threat detection on the Web. The framework is deployed within the TENSOR EU-funded project, and consists of an ontology and an adaptable semantic reasoning mechanism. We strongly believe that, in the short-and long-term, these techniques can greatly assist Law Enforcement Agencies in their investigational operations.

Advancing Counter-Terrorism: The Role of AI and ML in Detecting Online Threats

“…The sixth paper provides quantitative evidence of the effectiveness of Semantic Web technologies, reporting a significant reduction in the time required for threat detection by law enforcement agencies, from several hours to minutes in certain cases [6]. The seventh paper presents a comparative analysis, indicating that certain ML models can outperform others by 10-20% in accuracy and precision metrics, depending on the complexity of the dataset and the feature engineering involved [7].…”

“…The TENSOR project, which utilizes Semantic Web technologies, has reported improved information fusion capabilities, leading to a more accurate detection of terrorism-related content. The project claims an enhancement in the precision of detection by up to 30% compared to traditional web search tools [6].…”

Identifying the leaders and main conspirators of the attacks in terrorist networks

“…To illustrate their work, they used the 9-11 hijackers network, and their approach identified missing relationships among the members of the terrorist organization involved in the 9-11 attack. Mitzias and others [7] presented a unified semantic infrastructure for identifying the contents related to the terrorist activities available on the web. Their method uses ontology and the concept of adaptable semantic reasoning to understand the behaviors of terrorist networks.…”

“…Many methods for analyzing terrorist networks have been designed in the past few decades [2][3][4][5][6][7][8][9][10][11]. Certain good survey papers and studies on terrorist networks are available in existing literature [12][13][14][15][16][17][18][19][20].…”

The Not Yet Exploited Goldmine of OSINT: Opportunities, Open Challenges and Future Trends

“…As already mentioned throughout the previous Sections, the potentialities of the OSINT paradigm are quite broad. In fact, it is indeed possible to take advantage of the open data for cybersecurity and cyberdefence purposes, thus investigating the attackers and/or terrorist groups [90]. Nevertheless, the exploitation of the publicly-available data is prone to abuse.…”