Related papers: MLSTL-WSN: Machine Learning-based Intrusion Detect…
Software-defined network (SDN) is a new approach that allows network control to become directly programmable, and the underlying infrastructure can be abstracted from applications and network services. Control plane). When it comes to…
Indoor intrusion detection technology has been widely utilized in network security monitoring, smart city, entertainment games, and other fields. Most existing indoor intrusion detection methods directly exploit the Received Signal Strength…
Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS) play a critical role in protecting interconnected networks by detecting malicious actors and activities. Machine Learning (ML)-based behavior analysis…
Software-Defined Networking (SDN) is another technology that has been developing in the last few years as a relevant technique to improve network programmability and administration. Nonetheless, its centralized design presents a major…
Wireless Sensor Networks (WSNs) continue to experience rapid developments and integration into modern-day applications. Overall, WSNs collect and process relevant data through sensors or nodes and communicate with different networks for…
Operating in the ISM band, the wireless sensor network (WSN) risks being interfered by other concurrent networks. Our concerns are the technologies that do not perform listening before transmission such as Bluetooth, and the ones that do…
Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their personal data. This study explores the dynamic integration of Machine Learning (ML)…
Wireless mobile sensor networks (WMSNs) are groups of mobile sensing agents with multi-modal sensing capabilities that communicate over wireless networks. WMSNs have more flexibility in terms of deployment and exploration abilities over…
Network intrusion detection systems (NIDSs) play an important role in computer network security. There are several detection mechanisms where anomaly-based automated detection outperforms others significantly. Amid the sophistication and…
Wireless sensor networks (WSNs) are employed across a wide range of industrial applications where ultra-low power consumption is a critical prerequisite. At the same time, these systems must maintain a certain level of determinism to ensure…
With massive data being generated daily and the ever-increasing interconnectivity of the world's Internet infrastructures, a machine learning based intrusion detection system (IDS) has become a vital component to protect our economic and…
A sensor is a small electronic device which has the ability to sense, compute and communicate either with other sensors or directly with a base station (sink). In a wireless sensor network (WSN), the sensors monitor a region and transmit…
With more and more existing networks being transformed to Software-Defined Networking (SDN), they need to be more secure and demand smarter ways of traffic control. This work, SmartSecChain-SDN, is a platform that combines machine learning…
IEEE 802.1 Time-sensitive Networking~(TSN) standards are envisioned to replace legacy network protocols in critical domains to ensure reliable and deterministic communication over off-the-shelf Ethernet equipment. However, they lack…
Accurate indoor node localization is critical for practical Wireless Sensor Network (WSN) applications, as Global Positioning System (GPS) fails to provide reliable Line-of-Sight (LoS) conditions in most indoor environments. Real-world…
Wireless sensor networks (WSNs) have gained researchers' attention in the last several years. Small sensors powered by miniaturized microprocessors are capable of supporting several applications for civil and military domains. Determining…
Wireless Sensor Networks (WSN) is the collection of many small size low cost, battery operated sensor nodes distributed over the targeted region to collect the information of interest. We can say these networks can be a fruitful solution…
In this paper, we propose a Joint Semantic Transfer Network (JSTN) towards effective intrusion detection for large-scale scarcely labelled IoT domain. As a multi-source heterogeneous domain adaptation (MS-HDA) method, the JSTN integrates a…
Imbalanced datasets, where one class significantly outnumbers others, remain a persistent challenge in machine learning, often biasing predictions toward the majority class and degrading classifier performance. This paper provides a…
This paper proposes a novel federated learning approach for improving IoT network intrusion detection. The rise of IoT has expanded the cyber attack surface, making traditional centralized machine learning methods insufficient due to…