Security Issues in Internet of Medical Things
The notion of the Internet of Medical Things (IoMT) refers to a set of devices that create
interconnections between humans, equipment, sensors, and other systems, and thus …
interconnections between humans, equipment, sensors, and other systems, and thus …
Enhancing trustworthiness among iot network nodes with ensemble deep learning-based cyber attack detection
S Malathi, SR Begum - Expert Systems with Applications, 2024 - Elsevier
A lot of machine learning methods and expert systems are used in network intrusion
detection automation. When different industrial control systems merge with the Internet of …
detection automation. When different industrial control systems merge with the Internet of …
BRL-ETDM: Bayesian reinforcement learning-based explainable threat detection model for industry 5.0 network
To enhance the universal adaptability of the Real-Time deployment of Industry 5.0, various
machine learning-based cyber threat detection models are given in the literature. Most of the …
machine learning-based cyber threat detection models are given in the literature. Most of the …
Robust intrusion detection for network communication on the Internet of Things: a hybrid machine learning approach
The importance and growth of the Internet of Things (IoT) in computer networks and
applications have been increasing. Additionally, many of these applications generate large …
applications have been increasing. Additionally, many of these applications generate large …
SmartSentry: Cyber Threat Intelligence in Industrial IoT
S Sadhwani, UK Modi, R Muthalagu, PM Pawar - IEEE Access, 2024 - ieeexplore.ieee.org
While the Internet of Things (IoT) paradigm has transformed connectivity, it has also brought
with it previously unheard-of security risks. The categorization of IoT attacks using several …
with it previously unheard-of security risks. The categorization of IoT attacks using several …
Graph-ensemble fusion for enhanced IoT intrusion detection: leveraging GCN and deep learning
K Mittal, P Khurana Batra - Cluster Computing, 2024 - Springer
The proliferation of Internet of Things (IoT) applications has heightened the vulnerability of
information security, making it susceptible to attacks that may lead to the compromise of …
information security, making it susceptible to attacks that may lead to the compromise of …
A collaborative intrusion detection approach based on deep learning and blockchain
C Hazman, S Amaouche, M Abdedaime… - … and machine learning …, 2024 - taylorfrancis.com
Intrusion detection systems developed in the past few years could identify a wide range of
harmful network assaults using a number of monitoring methodologies. Still, existing …
harmful network assaults using a number of monitoring methodologies. Still, existing …
A machine learning-based ensemble model for securing the IoT network
R Singh, KP Sharma, LK Awasthi - Cluster Computing, 2024 - Springer
The rapidly growing number of Internet of Things (IoT) devices has led to a rise in data
transfers, which has raised security concerns. Due to the devices' limited processing …
transfers, which has raised security concerns. Due to the devices' limited processing …
Federated transfer learning for intrusion detection system in industrial iot 4.0
JIR NR - Multimedia Tools and Applications, 2024 - Springer
A major concern for Industry 4.0 is security issues because of several new cyber-security
risks. In recent eras, various Deep Learning methods have been applied for intrusion …
risks. In recent eras, various Deep Learning methods have been applied for intrusion …
A Collaborative Anomaly Detection Model Using En-Semble Learning and Blockchain
Abstract Intrusion Detection Systems (IDS) have historically been constructed using a
centralized topology in which a single device monitors the whole network. However, as the …
centralized topology in which a single device monitors the whole network. However, as the …