With the continuous expansion and evolution of IoT applications, attacks on those IoT
applications continue to grow rapidly. In this systematic literature review (SLR) paper, our …

With the continuous increase in cyberattacks over the past few decades, the quest to
develop a comprehensive, robust, and effective intrusion detection system (IDS) in the …

The significance of an intrusion detection system (IDS) in networks security cannot be
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …

This study explores integrating blockchain technology into the Internet of Medical Things
(IoMT) to address security and privacy challenges. Blockchain's transparency …

Botnets, groups of malware-infected hosts controlled by malicious actors, have gained
prominence in an era of pervasive computing and the Internet of Things. Botnets have …

The majority of the intrusion detection solutions proposed using machine learning and deep
learning approaches are based on known attack classes only. Comprehensive threat …

DDoSim, a simulation testbed for mimicking real-world, large-scale botnet DDoS attacks, is
presented. DDoSim offers various capabilities, including running user-specified software …

Abstract The incorporation of Artificial Intelligence (AI) into the fields of Neurosurgery and
Neurology has transformed the landscape of the healthcare industry. The present study …

Optimization of resource consumption and decreasing the response time of authentication
requests is an immense urgent requirement for supporting the scalability of resources in IoT …

Currently, within the world, cybercrime is becoming increasingly rampant—often targeting
civil infrastructure like power stations and other critical systems. A trend that is being noticed …