An artificial neural network based fault detection and diagnosis for wireless mesh networks

Yaqini, Akmal; Popalyar, Freshta

doi:10.1109/wd.2018.8361704

Cited by 6 publications

(6 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The transmitter creates a unique identifier or authentication code using a shared symmetric key with the receiver node. The receiver subsequently computes the MAC code using the identical key and compares it with the received MAC code to determine whether the source is authentic [22,36,37,44].…”

Section: Authentication Mechanismmentioning

confidence: 99%

“…Here are some approaches for intrusion detection using ML in WSNs: Support Vector Machines (SVMs), k-Nearest Neighbor algorithm (KNN), hybrid detection, reinforcement learning, and transfer learning. However, the problem remains with the machine learning training process, so many studies have attempted to improve it by decreasing training time, depending on a small data set, and enhancing accuracy [1,5,14,15,22,23,37,44,53].…”

Section: Intrusion Detection System (Ids)mentioning

confidence: 99%

“…It is possible to develop accurate and reliable malicious node detection mechanisms that can help detect and prevent attacks by malicious nodes in WSNs. All these techniques aim to improve the security and reliability of WSNs and prolonging the network's lifespan [23,31,36,44,55].…”

Section: Malicious Node Detectionmentioning

confidence: 99%

“…Because of the unique constraints and limited resources involved in deploying the sensor nodes, security in WSNs poses additional challenges than in conventional wireless networks. Thus, the security issue is one of the major concerns with WSNs, and several research studies have been conducted to address it [1,14,21,22,23,25,36,37,38,44]. Here are the most important open issues and future directions in the security of WSNs, as depicted in Fig.…”

Section: Future Directions In Wsn Securitymentioning

confidence: 99%

See 3 more Smart Citations

A Review of Security Challenges and Solutions in Wireless Sensor Networks

Hassan,

Madkour,

Nouh

2023

Journal of Al-Azhar University Engineering Sector

View full text Add to dashboard Cite

Wireless Sensor Networks (WSNs) are a vital component of the Internet of Things (IoT) since it is a viable technology for a variety of real-time applications. This is mainly because WSNs are naturally distributed, low-cost, fault-tolerant, self-organizing, easily deployable, scalable, and function without a predefined infrastructure. Their applications include surveillance, smart power grids, traffic networks, telecommunications systems, smart cities, intelligent transportation, industrial quality control, and the military, to mention a few. However, the security of WSNs is a major concern due to their vulnerability to various types of attacks, including node compromise, eavesdropping, and denial-of-service. This paper covers the security issues in WSNs and discusses the security challenges faced by these networks and the existing solutions. It illustrates the possible attacks and explores the different security mechanisms that can be used to protect WSNs, including encryption, authentication, and key management. Trust and reputation management are presented being effective techniques for mitigating routing attacks, and the role of machine learning techniques in enhancing WSN security is outlined. The paper concludes by discussing future research directions in WSN security. The findings of this paper are valuable for researchers, network administrators, and policymakers who are involved in the design and implementation of secure WSNs.

show abstract

Section: Authentication Mechanismmentioning

confidence: 99%

Section: Intrusion Detection System (Ids)mentioning

confidence: 99%

Section: Malicious Node Detectionmentioning

confidence: 99%

Section: Future Directions In Wsn Securitymentioning

confidence: 99%

See 2 more Smart Citations

A Review of Security Challenges and Solutions in Wireless Sensor Networks

Hassan,

Madkour,

Nouh

2023

Journal of Al-Azhar University Engineering Sector

View full text Add to dashboard Cite

show abstract

“…In [29], a simple multicast ping mechanism for detecting damaged nodes in the ZigBee network is presented. In [30], failure detection in the mesh network was based on the use of artificial neural network. A previously trained neural network analyzes parameters, such as number of dropped packets, delay, and throughput reduction, and detects a failure based on them.…”

Section: Introductionmentioning

confidence: 99%

Phase Transitions in Wireless MESH Networks and Their Application in Early Detection of Network Coherence Loss

Paszkiewicz¹,

Bolanowski²,

Zapała³

2019

Applied Sciences

View full text Add to dashboard Cite

The paper focuses on the phenomenon of phase transitions related to changes taking place directly in a network structure; i.e., in physical topology. Although these changes are related to the physical layer, they directly affect the functioning of higher layers, and thus the quality and efficiency of network transmission. The research presented herein was focused in particular on phase transformations in MESH type wireless topologies. The dependence between the values of radius (transmitter power) nodes and the coherence of the MESH network is presented. These considerations are important for understanding the dynamics of processes occurring in topological structures, and for optimizing the use of power sources for individual nodes. The paper also presents the use of phase transition analysis for early detection of network coherence loss at the physical layer level. A new mechanism for assessing the level of network communication and an active method of preventing its failure using the arbiter and a set of limited diagnostic information are described. The solution presented can be used both in Internet of Things (IoT) systems and Industry 4.0 to create a high level of reliability wireless connection infrastructure between mobile and fixed devices.

show abstract