BACKGROUND: Advances in healthcare artificial intelligence (AI) are occurring rapidly and there is a growing discussion about managing its development. Many AI technologies end up owned and controlled by private entities. The nature of the implementa...
Computational intelligence and neuroscience
Sep 13, 2021
Network intrusion detection remains one of the major challenges in cybersecurity. In recent years, many machine-learning-based methods have been designed to capture the dynamic and complex intrusion patterns to improve the performance of intrusion de...
OBJECTIVES: Provide an overview of the emerging themes and notable papers which were published in 2020 in the field of Bioinformatics and Translational Informatics (BTI) for the International Medical Informatics Association Yearbook.
Cybersecurity is an arms race, with both the security and the adversaries attempting to outsmart one another, coming up with new attacks, new ways to defend against those attacks, and again with new ways to circumvent those defences. This situation c...
Successful cyber-attacks are caused by the exploitation of some vulnerabilities in the software and/or hardware that exist in systems deployed in premises or the cloud. Although hundreds of vulnerabilities are discovered every year, only a small frac...
Computational intelligence and neuroscience
Jun 15, 2021
Networks are exposed to an increasing number of cyberattacks due to their vulnerabilities. So, cybersecurity strives to make networks as safe as possible, by introducing defense systems to detect any suspicious activities. However, firewalls and clas...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2021
Deep learning is widely used in the medical field owing to its high accuracy in medical image classification and biological applications. However, under collaborative deep learning, there is a serious risk of information leakage based on the deep con...
The field of neuroimaging can greatly benefit from building machine learning models to detect and predict diseases, and discover novel biomarkers, but much of the data collected at various organizations and research centers is unable to be shared due...
The tiny encryption algorithm (TEA) is widely used when performing dissipative particle dynamics (DPD) calculations in parallel, usually on distributed memory systems. In this research, we reduced the computational cost of the TEA hash function and i...
IEEE transactions on neural networks and learning systems
Apr 2, 2021
The article considers the impulsive synchronization for inertial neural networks with unbounded delay and actuator saturation via sampled-data control. Based on an impulsive differential inequality, the difficulties caused by unbounded delay and impu...
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