NEW: A Dynamic and Self-Organized Artificial Swarm Intelligence Solution for Security and Privacy Threats in Healthcare ICT Infrastructures (AI4HEALTHSEC)
Funding source: EU Horizon 2020 Programme: 1/6/2020 – 30/6/2023
AI4HEALTHSEC proposes a state of the art solution that improves the detection and analysis of cyber-attacks and threats on HCIIs, and increases the knowledge on the current cyber security and privacy risks. Additionally, AI4HEALTHSEC builds risk awareness, within the digital Healthcare ecosystem and among the involved Health operators, to enhance their insight into their Healthcare ICT infrastructures and provides them with capability to react in case of security and privacy breaches. Last but not least AI4HEALTHSEC fosters the exchange of reliable and trusted incident-related information, among ICT systems and entities composing the HCIIs without revealing sensitive corporate details.
Cyber Security Incident Handling, Warning and Response System for the European Critical Infrastructures (CyberSANE)
Funding source: EU Horizon 2020 Programme: 1/9/2019 – 31/8/2022
Project website: https://www.cybersane-project.eu/
CyberSANE is aimed at developing a novel framework to improve the detection and analysis of cyber-attacks and threats on critical infrastructures and to increase the knowledge on the current cyber threat landscape. The framework will support human operators (such as Incident Response professionals) to dynamically increase preparedness, improve cooperation amongst CIIs operators, and adopt appropriate steps to manage security risks, report and handle security incidents.
Cyber security 4.0: protecting the Industrial Internet of Things (C4IoT)
Funding source: EU Horizon 2020 Programme: 1/6/2019 – 31/5/2022
Project website: https://www.c4iiot.eu/
C4IIoT is aimed at building and demonstrating a novel and unified IIoT cybersecurity framework for malicious and anomalous behaviour anticipation, detection, mitigation, and end-user informing. The framework provides a holistic and disruptive security-enabling solution for minimizing attack surfaces in IIoT systems, by exploiting (i) emerging security software and hardware protection mechanisms; (ii) state of the art machine and deep learning and privacy-aware analytics; (iii) novel encrypted network flow analysis; (iv) secure-by-design IIoT device fabrication; and (v) blockchain technologies, to provide a viable scheme for enabling security and accountability, preserving privacy, enabling reliability and assuring trustworthiness within IIoT applications. The C4IIoT framework will be demonstrated and validated on two carefully selected use cases in real world environments, namely Enabling security IIoT in (i) Inbound Logistics and (ii) a Smart Factory.
Resilient Transport Infrastructure to Extreme Events (RESIST)
Funding source: EU Horizon 2020 Programme: 1/9/2018 – 31/8/2021
Project website: http://www.resistproject.eu/
The overall goal of RESIST is to increase the resilience of seamless transport operation to natural and man-made extreme events, protect the users of the European transport infrastructure and provide optimal information to the operators and users of the infrastructure. The project will address extreme events on critical structures, implemented in the case of bridges and tunnels attacked by all types of extreme physical, natural and man-made incidents, and cyber-attacks. Sphynx’s contributions will in developing support for the security and resilience of critical infrastructures management systems against cyber-attacks.
Smart End-To-End Massive Iot Interoperability Connectivity and Security (SEMIOTICS)
Funding source: EU Horizon 2020 Programme: 1/1/2018 – 31/12/2020
Project website: https://www.semiotics-project.eu/
SEMIoTICS aims to develop a pattern-driven framework, built upon existing IoT platforms, to enable and guarantee secure and dependable actuation and semi-autonomic behaviour in IoT applications. Patterns encode proven dependencies between security, privacy, dependability and interoperability (SPDI) properties of individual smart objects and corresponding properties of orchestrations involving them. The SEMIoTICS framework will support cross-layer intelligent dynamic adaptation, including heterogeneous smart objects, networks and clouds, addressing effective adaptation and autonomic behaviour at field (edge) and infrastructure (backend) layers based on intelligent analysis and learning.
NEW: A comprehensive cyber-intelligence framework for resilient collaborative manufacturing systems (COLLABS)
Funding source: EU Horizon 2020 Programme: 1/1/2020 – 31/12/2022
Overview: The manufacturing ecosystem lacks a thorough cyber intelligence solution that addresses the key IIoT-related cybersecurity challenges towards a full realization of collaborative manufacturing in the context of Industry 4.0. COLLABS focuses on developing, validating, and demonstrating a comprehensive cyber-intelligence framework for collaborative manufacturing. This framework will enable secure data exchange across the digital supply chain while providing high degree of resilience, reliability, accountability and trustworthiness by addressing threat prevention, detection, mitigation, and real-time response. COLLABS is aimed at making significant scientific and technological advances in secure multi-party computation and homomorphic encryption, distributed deep learning and anomaly detection, distributed ledger technologies (blockchain) and smart contracts, and distributed remote software attestation.
A Cyber Security Platform for Virtualised 5G cyber range services (SPIDER)
Funding source: EU Horizon 2020 Programme: 1/7/2019 – 30/6/2022
Project website: https://spider-h2020.eu/
SPIDER delivers an innovative Cyber Range as a Service platform that extends and combines the capabilities of existing telecommunication testbeds and cyber ranges into a unified facility for (i) testing new security technologies, (ii) training modern cyber defenders in near real-world conditions, and (iii) supporting organizations and relevant stakeholders in making optimal cybersecurity investment decisions. At its core, it is a highly customizable dynamic network modeling instrument that enables real-life virtualization and real-time emulation of networks and systems. This will be complemented by cyber econometric capabilities, enabling users to forecast the evolution of attacks and their associated economic impact through the application of innovative risk analysis methodologies, econometric models and real-time attack emulation.
Cyber Security Threats and Threat Actors Training – Assurance Driven, Multi Layer, End-to-End Simulation and Training (THREAT-ARREST)
Funding source: EU Horizon 2020 Programme: 1/6/2018 – 31/5/2021
Project website: https://www.threat-arrest.eu/
THREAT-ARREST aims to develop an advanced training platform incorporating emulation, simulation, serious gaming, and visualization capabilities to adequately prepare stakeholders with different types of responsibility and levels of expertise in defending high-risk cyber systems and organizations to counter advanced, known and new cyber-attacks.
NEW: A cyber range training platform for medical organisations and systems security (AERAS)
Funding source: EU Horizon 2020 Programme (MCSA RISE): 1/12/2019 – 30/11/2023
AERAS aims to develop a realistic and rapidly adjustable cyber range platform for systems and organisations in the critical healthcare sector, to effectively prepare stakeholders with different types of responsibility and levels of expertise in defending high-risk, critical cyber-systems and organizations against advanced, known and new cyber-attacks, and reduce their security risks. The platform will be based on an evidence-based approach where virtual cyberwarfare and simulations are configured according to evidence regarding: (i) the occurrence of cyber threats, and (ii) the effectiveness of the operation of the internal and external system defense mechanisms. Evidence will be collected by multi- faceted real-time monitoring and assessed according to Cyber Range Security Assurance (CRSA) models specifying potential cyber-attacks, the security mechanisms used against them, and the methods for assessing their effectiveness. The AERAS solution will be delivered at TRL-7 and validated through two different pilots: (i) a hospital medical systems pilot; and (ii) a public health systems pilot.
HEALTHCARE / BIG DATA
NEW: A SECURE HEALTHCARE ENVIRONMENT FOR INFORMATICS RESILIENCE (HEIR)
Funding source: EU Horizon 2020 Programme
HEIR is to provide 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.
Smart Big Data Platform to Offer Evidence-based Personalised Support for Healthy and Independent Living at Home (SMART BEAR)
Funding source: EU Horizon 2020 Programme: 1/7/2019 – 30/6/2023
Project website: https://www.smart-bear.eu/
SMART BEAR will develop an innovative platform with off-the-shelf smart and medical devices, at TRL9, to support the healthy and independent living of elderly people with five prevalent health-related conditions; Hearing Loss, Cardio Vascular Diseases, Cognitive Impairments, Mental Health Issues, and Balance Disorders, as well as Frailty. This will be achieved through intelligent, evidenced-based interventions on lifestyle, medically-significant risk factors, and chronic disease management, enabled by the utilisation of continuous and objective medical and environment sensing, assistive technologies and big data analytics. The platform will be validated through five large scale pilots, involving five different countries and 5.000 individuals.
HOLOgrams for personalised virtual coaching and motivation in an ageing population with BALANCE disorders (HOLOBALANCE)
Funding source: EU Horizon 2020 Programme: 1/12/2017 – 30/11/2020
Project website: https://holobalance.eu/
The overall objective of HOLOBALANCE is to develop and validate a new personalized hologram coach platform for virtual coaching, motivation and empowerment of the ageing population with balance disorders. The coaching part will be realised by holograms and augmented reality games, along with easy to use sensors (smart bracelet, smart glasses, sensorized soles) that can be customized to implement and coach the user with specific, individualized exercises, offering new forms of accessible user interaction. Sphynx Technology Solutions is responsible for the security and privacy of the platform.
Unification of treatments and Interventions for Tinnitus patients (UNITI)
Funding source: EU Horizon 2020 Programme: 1/1/2020 – 31/12/2022
Project website: http://uniti.tinnitusresearch.net/
UNITI’s overall aim is to deliver a predictive computational model based on existing and longitudinal data attempting to address the question which treatment approach is optimal for a Tinnitus patient based on specific parameters. Clinical, epidemiological, medical, genetic and audiological data, including signals reflecting ear-brain communication, will be analysed from existing databases. Predictive factors for different patient groups will be extracted and their prognostic relevance will be tested in a randomized controlled trial (RCT) in which different groups of patients will undergo a combination of therapies targeting the auditory and central nervous systems. Sphynx’s role in the project will be to support the integration of heterogeneous databases in a federated (big) data repository and the provision of security assurance for the system to be developed to provide data analytics in the project.
Artificial intelligence supporting cancer patients across Europe (ASCAPE)
Funding source: EU Horizon 2020 Programme: 1/1/2020 – 31/12/2022
Overview: The main objective of ASCAPE is to take advantage of the recent ICT advances in Big Data, Artificial Intelligence and Machine Learning to support cancer patients’ quality of life and health status. To achieve its objective, ASCAPE will create an open AI infrastructure that will enable health stakeholders (hospitals, research institutions, companies, etc.) to deploy and execute its AI algorithms locally on their private data. Any new knowledge produced by this process will be sent back to the open AI infrastructure. This way the knowledge will be shared among everyone while the medical data will still remain private. The services to be designed, piloted and deployed inside this project will include intelligent interventions for physiological and psychological support, improved patient and family counselling and guidance, early diagnosis and forecasts of ill-health, identification of disease trajectories and relapse, and improved health literacy.
Biologically Inspired Complex Software System Reconstruction at Near Extinction States (BIO_PHOENIX)
Funding source: EU Horizon 2020 Programme (MCSA-RISE): 1/7/2019 – 30/6/2022
Project website: https://www.bio-phoenix.eu/
Bio-Phoenix aims to develop a bio-inspired paradigm for reconstructing nearly extinct complex software systems based on a novel computational DNA (co-DNA) oriented systems modelling approach. The co-DNA will encapsulate logic and program code and will enable the use of analogues of biological processes for transmitting, transforming, combining, activating and deactivating it across computational and communication devices. The purpose of encoding the co- DNA of a system, and computational analogues of biological processes using it, is to enable other computational devices receiving the co-DNA to act as parts of the system that needs to be reconstructed, realise its functionality, and spread further the system reconstruction process.