Reinforcement Learning (RL) is a machine learning (ML) technique to learn sequential
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …

Healthcare information security is becoming a significant responsibility for all healthcare
organisations and individuals. Innovative medical equipment and healthcare apps are vital …

There exists a rising concern on security of healthcare data and service. Even small lost,
stolen, displaced, hacked, or communicated in personal health data could bring huge …

Recent advances in the Internet of Medical Things (IoMT) have impacted traditional medical
treatment and have evolved data communications in the Smart Healthcare scenario …

Coexploitation behavior, referring to multiple software vulnerabilities being exploited jointly
by one or more exploits, brings enormous challenges to the prevention and remediation of …

Abstract The Internet of Medical Things (IoMT) is a bionetwork of allied medical devices,
sensors, wearable biosensor devices, etc. It is gradually reforming the healthcare industry by …

Network assaults pose significant security concerns to network services; hence, new
technical solutions must be used to enhance the efficacy of intrusion detection systems …

Large unbalanced datasets pose challenges for machine learning models, as redundant
and irrelevant features can hinder their effectiveness. Furthermore, the performance of …

In this article, aiming at a Chinese keyword-based book search service, from a technological
perspective, we propose to modify a user query sequence carefully to confuse the user …

Deformable contours are widely applied in medical image segmentation, which are usually
derived from appearance cues in medical images. However, the performance of deformed …