Covert evidence gathering has not seen major changes in decades. Law enforcement Agencies (LEAs) are still using conventional, manpower based techniques to gather forensic evidence. Concealed surveillance devices can provide irrefutable evidences, but current video surveillance systems are usually bulky and complicated, are often used as simple video recorders, and require complex, expensive infrastructure to supply power, bandwidth, storage and illumination. Recent years have seen significant advances in the surveillance industry, but these were rarely targeted to forensic applications. The imaging community is fixated on cameras for mobile phones, where the figures of merit are resolution, image quality, and low profile. A mobile phone with its camera on would consume its battery in under two hours. Industrial surveillance cameras are even more power hungry, while intelligent algorithms such as face detection often require extremely high processing power, such as backend server farms, and are not available in conventional surveillance systems. Here we propose to develop and validate a novel, ultra-low-power, intelligent, miniaturised, low-cost, wireless, autonomous sensor (“FORENSOR”) for evidence gathering. Its ultra-sensitive camera and built-in intelligence will allow it to operate at remote locations, automatically identify pre-defined criminal events, and alert LEAs in real time while providing and storing the relevant video, location and timing evidence. FORENSOR will be able to operate for up to two months with no additional infrastructure. It will be manageable remotely, preserve the availability and the integrity of the collected evidence, and comply with all legal and ethical standards, in particular those related to privacy and personal data protection. The combination of built-in intelligence with ultra-low power consumption could help LEAs take the next step in fighting severe crimes.

The advent of Social Networks has made both companies and public bodies tremendously exposed to the so-called Social Engineering 2.0, and thus prone to targeted cyber-attacks. Unfortunately, there is currently no solution available on the market that allows neither the comprehensive assessment of Social Vulnerabilities nor the management and reduction of the associated risk. DOGANA aims to fill this gap by developing a framework that delivers "aDvanced sOcial enGineering And vulNerability Assessment". The underlying concept of DOGANA is that Social Vulnerabilities Assessments (SVAs), when regularly performed with the help of an efficient framework, help deploy effective mitigation strategies and lead to reducing the risk created by modern Social Engineering 2.0 attack techniques. Two relevant features of the proposed framework are: i) the presence of the "awareness" component within the framework as the cornerstone of the mitigation activities; ii) the legal compliance by design of the whole framework, that will be ensured by a partner and a work package explicitly devoted to this task. Moreover, the outcomes of the project are also expected to provide a solid basis to revise the insurance models for cyber-attacks related risks, thanks to the involvement of 2 strong DOGANA partners in this area of activity. The project will be implemented by a consortium of 18 partners, from 11 different countries, including users, technology providers of whom 3 are major world-wide cyber-security solutions market leaders as well as legal and psychological expertise. An extensive field trial plan enables the testing of the DOGANA platform with six users (4 partners and 2 supporting users) operating in the critical areas of energy, finance, transport, utilities, and public authorities. DOGANA has also created a unique consortium with a world-wide scope.

SCENE is building an integrated security system for vehicular network, for both IoT based data collection and multimedia secured content delivery. The content delivery platform is intelligent enough to be deployed in both IoT mode and in the stand alone mode to deliver contents to subscribed smart application. SCENE adopts a radically different view on the type of infrastructure needed for mid-size municipalities : SCENE is an open mobile platform for smart city applications, supporting different IoT wireless access networks (while providing an excellent level of infrastructure cybersecurity. By using the public transport network, municipalities will achieve complete coverage with less investment in infrastructure. SCENE is based on six pillars:, security, system integrity, scalability, elasticity, visualization, interoperability with external services, and easy management. In order to achieve these six pillars, four modules will be introduced. A security module for both data and communication which will be provided by CEA. Second, a smart gateway for mobile IoT/Content delivery control, aggregation and transmission provided by JCPC. The proposed gateway ensures both scalability and elasticity. Third, a service platform that proposes a powerful IoT oriented architecture to provide interoperability and added value services for integration and data analytics, ensuring scalability and elasticity of the system as well as system integrity by ALMAVIVA. The proposed service platform supports integrated data analytics services among other services. Aa dashboard module is introduced to ensure the ease of management of all system components as well as data visualization. The overall system integration will be implemented by VISIONWARE together with the different municipalities involved. The bus network of Catania in the Italian Sicily Region will be the first SCENE field trial, coupled with a field trial in Rennes city in France, and in Portugal.