Real‐time threat assessment based on hidden Markov models

Abstract

An essential factor toward ensuring the security of individuals and critical infrastructures is the timely detection of potentially threatening situations. To this end, especially in the law enforcement context, the availability of effective and efficient threat assessment mechanisms for identifying and eventually preventing crime‐ and terrorism‐related threatening situations is of utmost importance. Toward this direction, this work proposes a hidden Markov model‐based threat assessment framework for effectively and efficiently assessing threats in specific situations, such as public events. Specifically, a probabilistic approach is adopted to estimate the threat level of a situation at each point in time. The proposed approach also permits the reflection of the dynamic evolution of a threat over time by considering that the estimation of the threat level at a given time is affected by past observations. This estimation of the dynamic evolution of the threat is very useful, since it can support the decisions by security personnel regarding the taking of precautionary measures in case the threat level seems to adopt an upward trajectory, even before it reaches the highest level. In addition, its probabilistic basis allows for taking into account noisy data. The applicability of the proposed framework is showcased in a use case that focuses on the identification of potential threats in public events on the basis of evidence obtained from the automatic visual analysis of the footage of surveillance cameras.

Artificial Intelligence to Counter Cyber-Terrorism

“…Powerful explainable AI techniques [24] leveraging the outputs produced by the aforementioned multimodal AI models support human interpretation, providing HSP moderators and LEA analysts with reasoning and explanation on the results delivered by the AI solutions, thus helping towards making informed decisions related to the removal of abusive content from the online space. Finally, threat assessment tools [25] help HSP moderators and LEA analysts towards assessing the severity of threats posted online, thus enforcing the appropriate measures including the removal of such material.…”