PREVISION

With the advent of the internet, many forms of traditional crime have become increasingly digitised. For example, terrorists, Organised Crime Groups (OCGs) and cybercriminals are deploying and adapting new technologies, such as social media, the Darknet, and the Internet of Things (IoT), as instruments to perform or facilitate criminal acts.

Terrorists, Organised Crime Groups and cybercriminals often leave a cyber trail that can be used to track them down. However, it is often very difficult for law enforcement officers to pull together all of the disparate data sources in order to perform comprehensive, coherent analysis.

The use of encryption, information hiding and other anti-forensic techniques in online communication means the challenge of acquiring and analysing digital evidence to predict deviant behaviour is increasingly difficult.

How can we empower law enforcement agencies (LEAs) with supreme analytical and predictive capabilities to combat digital crime?

The PREVISION project will develop a platform for extreme-scale data analytics with the capacity to crawl and analyse vast amounts of data from multiple streams, such as the open web, the Darknet, social networks, surveillance and CCTV systems.

The PREVISION platform will support LEAs to predict and detect deviant behaviour by:

• Analysing massive data streams, from various online sources
• Creating knowledge graphs that capture the structure, interrelations and trends of terrorists, organised crime groups, and cybercriminals
• Predicting abnormal or deviant behaviour, based on psychological, sociological and linguistic models in conjunction with historical data patterns
• Maintaining high situation awareness, using visual analytics and human-machine interaction

Trilateral assesses the ethical issues that could arise in relation to cybercrime and terrorism throughout the development and implementation of the PREVISION platform.

Trilateral considers to what extent the project’s proposed technological solutions – focused on analysing and processing multiple heterogenous data streams – are aligned with European societal values and the measures needed to mitigate and avoid any harm to ethics or fundamental rights.

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