AI4HEALTHSEC | A Dynamic and Self-Organized Artificial Swarm Intelligence Solution for Security and Privacy Threats in Healthcare ICT Infrastructures

Summary
The increasing interconnection of technology in healthcare between devices at the physical and cyber levels has transformed these infrastructures into large Health Care Information Infrastructures. Such HCIIs are considered critical and sensitive infrastructures due to their importance for people’s well-being and safety. On the other hand, the evolving digital interconnectivity has also changed the threat landscape, producing a wide range of security and privacy challenges and increasing the danger of potential cybersecurity attacks. The integrated nature introduces new potential entry points for cybersecurity risks. Thus, there is an urgent, pressing need for the Health operators to protect their HCIIs. Efficient situational awareness, incident handling and risk assessment is an important step to acquiring a thorough and common understanding of cyber-attack situations, and is necessary to timely reveal security events and data breaches occurring into HCIIs. Consequently, analysis of incident information is crucial in attempting to detect the presence of a threat, within HCIIs, that has already been detected in other interdependent systems within the same ecosystem.
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
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Web resources: https://cordis.europa.eu/project/id/883273
Start date: 01-10-2020
End date: 31-12-2023
Total budget - Public funding: 4 998 948,00 Euro - 4 998 948,00 Euro
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Original description

The increasing interconnection of technology in healthcare between devices at the physical and cyber levels has transformed these infrastructures into large Health Care Information Infrastructures. Such HCIIs are considered critical and sensitive infrastructures due to their importance for people’s well-being and safety. On the other hand, the evolving digital interconnectivity has also changed the threat landscape, producing a wide range of security and privacy challenges and increasing the danger of potential cybersecurity attacks. The integrated nature introduces new potential entry points for cybersecurity risks. Thus, there is an urgent, pressing need for the Health operators to protect their HCIIs. Efficient situational awareness, incident handling and risk assessment is an important step to acquiring a thorough and common understanding of cyber-attack situations, and is necessary to timely reveal security events and data breaches occurring into HCIIs. Consequently, analysis of incident information is crucial in attempting to detect the presence of a threat, within HCIIs, that has already been detected in other interdependent systems within the same ecosystem.
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

Status

SIGNED

Call topic

SU-DS05-2018-2019

Update Date

27-10-2022
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