Ensuring public spaces safety while preserving the freedom of citizens represents a challenge for European societies. Soft targets like malls, stadiums or big events continue to face a variety of evolving cyber and physical threats. To secure public spaces and other soft targets requires an integral security approach and new concepts involving all the security actors along with private operators. APPRAISE aims to build on the latest advances in big data analysis, artificial intelligence, and advanced visualisation to create an integral security framework that will improve both the cyber/physical security and safety of public spaces by enabling a proactive, integrated, risk-based, and resilience-oriented approach. This framework will be designed to support the secured private-public collaboration and optimise the coordination of operations involving private security staff, private operators, and law enforcement agencies.

APPRAISE will offer unprecedented capabilities to predict and identify criminal and terrorist acts and enhance the operational collaboration of security actors before, during, and after an incident occurs. Social, Ethical, Legal, and Privacy observatories bringing together LEAs, private operators, technology experts, psychologists, sociologists, and society representatives will ensure full conformity of the developed tools with current EU legislation and citizens’ acceptance, preparing the ground for successful expl oitation.

The consortium consists of world-class research centres, industries, SMEs, LEAs of different types (national police, municipal police, elite tactical unit) as well as private security practitioners and operators, coordinated by a large industrial company with a leading position in the security market.

APPRAISE will demonstrate its solutions in four complementary pilot sites: a tennis tournament in Italy, a transnational cycling tour with stages in France and Spain, an international fair in Poland, and a mall in Slovenia.

ΜΚLab leads the Work Package related to Internet content analysis tools for threat intelligence and will be responsible for the data acquisition and pre-processing from surface and deep web sources. Moreover, ΜΚLab will be responsible for activities related to trend detection and predictive analytics, and will contribute significantly to activities related to the Identification of relevant people and criminal groups from online content. Finally, ΜΚLab will contribute to other technical tasks and in the deployment and validation of the solution in operational environments.