The health sector is steadily becoming the de facto target for cyberattacks. Based on the most recent ENISA report at the end of 2018, cybersecurity incidents have shown that the healthcare sector is one of the most vulnerable. Focusing specifically on Electronic Medical Devices (EMD), they suffer from numerous and multi-layered vulnerabilities . Default, weak or no password authentication for remote connections, unencrypted traffic or obsolete and insecure cryptographic algorithms, unsupported operating systems, outdated, unmanaged and vulnerable software are among the most serious problems that jeopardise both their smooth operation and the data aggregated and stored. The vision of HEIR is to provide a thorough threat identification and cybersecurity knowledge base system addressing both local (in the hospital / medical centre) and global (including different stakeholders) levels, that comprises the following pillars: (i) Real time threat hunting services, facilitated by advanced machine learning technologies, supporting the identification of the most common threats in electronic medical systems based on widely accepted methodologies such as the OWASP Top 10 Security Risks and the ENISA Top 15 Threats; (ii) Sensitive data trustworthiness sharing facilitated by the HEIR privacy aware framework; (iii) Innovative Benchmarking based on the calculation of the Risk Assessment of Medical Applications (RAMA) score, that will measure the security status of every medical device and provide thorough vulnerability assessment of hospitals and medical centres; (iv) The delivery of an Observatory for the Security of Electronic Medical Devices; an intelligent knowledge base accessible by different stakeholders, providing advanced visualisations for each threat identified in RAMA and facilitating global awareness on EMD-related threats. Last, HEIR will set up a broad European network for establishing good security practice in all regulatory frameworks to reduce market access.

The data generated in the health domain is coming from heterogeneous, multi-modal, multi-lingual, dynamic and fast evolving medical technologies. Today we are found in a big health landscape characterized by large volume, versatility and velocity (3Vs) which has led to the evolution of the informatics in the big biodata domain. AEGLE project will build an innovative ICT solution addressing the whole data value chain for health based on: cloud computing enabling dynamic resource allocation, HPC infrastructures for computational acceleration and advanced visualization techniques. AEGLE will: - Realize a multiparametric platform using algorithms for analysing big biodata including features such as volume properties, communication metrics and bottlenecks, estimation of related computational resources needed, handling data versatility and managing velocity - Address the systemic health big bio-data in terms of the 3V multidimensional space, using analytics based on PCA techniques - Demonstrate AEGLE’s efficiency through the provision of aggregated services covering the 3V space of big bio-data. Specifically it will be evaluated in: a)big biostreams where the decision speed is critical and needs non-linear and multi-parametric estimators for clinical decision support within limited time, b)big-data from non-malignant diseases where the need for NGS and molecular data analytics requires the combination of cloud located resources, coupled with local demands for data and visualization, and finally c)big-data from chronic diseases including EHRs and medication, with needs for quantified estimates of important clinical parameters, semantics’ extraction and regulatory issues for integrated care - Bring together all related stakeholders, leading to integration with existing open databases, increasing the speed of AEGLE adaptation - Build a business ecosystem for the wider exploitation and targeting on cross-border production of custom multi-lingual solutions based on AEGLE.