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Model for cyber security information sharing in healthcare sector
(Institute of Electrical and Electronics Engineers, 2020)
In the modern society almost all services are based on data-networks and networked systems. Especially through the growing digitalization an increasing number of services is connected to data-networks. One example of a ...
Measuring Learning in a Cyber Security Exercise
(Association for Computing Machinery, 2020)
In recent years, cyber security exercises have established themselves as an integral part of cyber security education. Cyber security professionals usually work as a part of a team that monitors and responds to incidents ...
Review of pedagogical principles of cyber security exercises
(2020)
Modern digitalized cyber domains are extremely complex ensemble. Cyber attacks or incidents against system may affect capricious effects for another system or even for physical devices. For understanding and training to ...
Comprehensive cyber arena; the next generation cyber range
(IEEE, 2020)
The cyber domain and all the interdependencies between networked systems form an extremely complex ensemble. Incidents in the cyber domain may have an abundance effect on the physical domain. For example, a cyber attack ...
Cyber range: preparing for crisis or something just for technical people?
(Academic conferences international, 2021)
Digitalization has increased the significance of cybersecurity within the current highly interconnected society. The number and complexity of different cyber-attacks as well as other malicious activities has increased ...
Color-optimized one-pixel attack against digital pathology images
(Fruct oy, 2021)
Modern artificial intelligence based medical imaging tools are vulnerable to model fooling attacks. Automated medical imaging methods are used for supporting the decision making by classifying samples as regular or as ...
One-pixel attacks against medical imaging: a conceptual framework
(Springer, 2021)
This paper explores the applicability of one-pixel attacks against medical imaging. Successful attacks are threats that could cause mistrust towards artificial intelligence solutions and the healthcare system in general. ...
Model fooling attacks against medical imaging: a short survey
(ProCon, 2020)
This study aims to find a list of methods to fool artificial neural networks used in medical imaging. We collected a short list of publications related to machine learning model fooling to see if these methods have been ...
Modelling medical devices with honeypots
(Springer, 2020)
Cyber security is one of the key priorities in the modern digitalised and complex network totality. One of the major domains of interest is the healthcare sector where a cyber incident may cause unprecedented circumstances. ...
Statistical evaluation of artificial intelligence -based intrusion detection system
(Springer, 2020)
Training neural networks with captured real-world network data may fail to ascertain whether or not the network architecture is capable of learning the types of correlations expected to be present in real data.
In this ...