scholarly journals Fault-Tolerant Anomaly Detection Method in Wireless Sensor Networks

Information ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 236 ◽  
Author(s):  
Nengsong Peng ◽  
Weiwei Zhang ◽  
Hongfei Ling ◽  
Yuzhao Zhang ◽  
Lixin Zheng
Keyword(s):  
Sensor Networks ◽  
Anomaly Detection ◽  
Sensor Network ◽  
Detection Method ◽  
Fault Tolerant ◽  
False Negative ◽  
False Negative Rate ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Wireless Sensor

A key issue in wireless sensor network applications is how to accurately detect anomalies in an unstable environment and determine whether an event has occurred. This instability includes the harsh environment, node energy insufficiency, hardware and software breakdown, etc. In this paper, a fault-tolerant anomaly detection method (FTAD) is proposed based on the spatial-temporal correlation of sensor networks. This method divides the sensor network into a fault neighborhood, event and fault mixed neighborhood, event boundary neighborhood and other regions for anomaly detection, respectively, to achieve fault tolerance. The results of experiment show that under the condition that 45% of sensor nodes are failing, the hit rate of event detection remains at about 97% and the false negative rate of events is above 92%.

scholarly journals Anomaly Detection in Medical Wireless Sensor Networks using SVM and Linear Regression Models

2016 ◽  
pp. 466-486 ◽  
Author(s):  
Osman Salem ◽  
Alexey Guerassimov ◽  
Ahmed Mehaoua ◽  
Anthony Marcus ◽  
Borko Furht
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
False Negative ◽  
Patient Data ◽  
Machine Learning Algorithms ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Smart Device

This paper details the architecture and describes the preliminary experimentation with the proposed framework for anomaly detection in medical wireless body area networks for ubiquitous patient and healthcare monitoring. The architecture integrates novel data mining and machine learning algorithms with modern sensor fusion techniques. Knowing wireless sensor networks are prone to failures resulting from their limitations (i.e. limited energy resources and computational power), using this framework, the authors can distinguish between irregular variations in the physiological parameters of the monitored patient and faulty sensor data, to ensure reliable operations and real time global monitoring from smart devices. Sensor nodes are used to measure characteristics of the patient and the sensed data is stored on the local processing unit. Authorized users may access this patient data remotely as long as they maintain connectivity with their application enabled smart device. Anomalous or faulty measurement data resulting from damaged sensor nodes or caused by malicious external parties may lead to misdiagnosis or even death for patients. The authors' application uses a Support Vector Machine to classify abnormal instances in the incoming sensor data. If found, the authors apply a periodically rebuilt, regressive prediction model to the abnormal instance and determine if the patient is entering a critical state or if a sensor is reporting faulty readings. Using real patient data in our experiments, the results validate the robustness of our proposed framework. The authors further discuss the experimental analysis with the proposed approach which shows that it is quickly able to identify sensor anomalies and compared with several other algorithms, it maintains a higher true positive and lower false negative rate.

scholarly journals Redundancy Analysis and a Distributed Self-Organization Protocol for Fault-Tolerant Wireless Sensor Networks

2007 ◽  
Vol 3 (3) ◽  
pp. 243-272 ◽  
Author(s):  
Yi Zou ◽  
Krishnendu Chakrabarty
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Fault Tolerant ◽  
Selection Procedure ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Self Organization ◽  
Distributed Sensor ◽  
Node Failures

Sensor nodes in a distributed sensor network can fail due to a variety of reasons, e.g., harsh environmental conditions, sabotage, battery failure, and component wear-out. Since many wireless sensor networks are intended to operate in an unattended manner after deployment, failing nodes cannot be replaced or repaired during field operation. Therefore, by designing the network to be fault-tolerant, we can ensure that a wireless sensor network can perform its surveillance and tracking tasks even when some nodes in the network fail. In this paper, we describe a fault-tolerant self-organization scheme that designates a set of backup nodes to replace failed nodes and maintain a backbone for coverage and communication. The proposed scheme does not require a centralized server for monitoring node failures and for designating backup nodes to replace failed nodes. It operates in a fully distributed manner and it requires only localized communication. This scheme has been implemented on top of an energy-efficient self-organization technique for sensor networks. The proposed fault-tolerance-node selection procedure can tolerate a large number of node failures using only localized communication, without losing either sensing coverage or communication connectivity.

Technology Research on the Fault Diagnosis of Wireless Sensor Network System

2013 ◽  
Vol 846-847 ◽  
pp. 442-445
Author(s):  
Chun Lin He
Keyword(s):  
Fault Diagnosis ◽  
Sensor Network ◽  
Simulation Experiment ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network System ◽  
Technology Research ◽  
Spatio Temporal ◽  
Network Fault

The fault diagnosis technology have emerged and developed rapidly with the development of wireless sensor networks and requirements of applications improve. This paper describes two commonly used sensor network fault modeling. What is more, in order to solve this problem that sensor nodes are vulnerable and therefore produce wrong data, the paper proposes a distributed fault detecting algorithm based on spatio-temporal correlation among data of adjacent nodes. The simulation experiment shows that the algorithm can efficiently detect errors in the network and very few errors are introduced.

scholarly journals Anomaly Detection in Medical Wireless Sensor Networks using SVM and Linear Regression Models

2014 ◽  
Vol 5 (1) ◽  
pp. 20-45 ◽  
Author(s):  
Osman Salem ◽  
Alexey Guerassimov ◽  
Ahmed Mehaoua ◽  
Anthony Marcus ◽  
Borko Furht
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
Patient Data ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Smart Devices ◽  
Support Vector ◽  
Processing Unit

This paper details the architecture and describes the preliminary experimentation with the proposed framework for anomaly detection in medical wireless body area networks for ubiquitous patient and healthcare monitoring. The architecture integrates novel data mining and machine learning algorithms with modern sensor fusion techniques. Knowing wireless sensor networks are prone to failures resulting from their limitations (i.e. limited energy resources and computational power), using this framework, the authors can distinguish between irregular variations in the physiological parameters of the monitored patient and faulty sensor data, to ensure reliable operations and real time global monitoring from smart devices. Sensor nodes are used to measure characteristics of the patient and the sensed data is stored on the local processing unit. Authorized users may access this patient data remotely as long as they maintain connectivity with their application enabled smart device. Anomalous or faulty measurement data resulting from damaged sensor nodes or caused by malicious external parties may lead to misdiagnosis or even death for patients. The authors' application uses a Support Vector Machine to classify abnormal instances in the incoming sensor data. If found, the authors apply a periodically rebuilt, regressive prediction model to the abnormal instance and determine if the patient is entering a critical state or if a sensor is reporting faulty readings. Using real patient data in our experiments, the results validate the robustness of our proposed framework. The authors further discuss the experimental analysis with the proposed approach which shows that it is quickly able to identify sensor anomalies and compared with several other algorithms, it maintains a higher true positive and lower false negative rate.

scholarly journals DOS Attacks on TCP/IP Layers in WSN

2013 ◽  
Vol 1 (2013) ◽  
pp. 40-45
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Low Cost ◽  
Denial Of Service ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Renewable Energy Resources ◽  
Dos Attack ◽  
Dos Attacks

The emergence of sensor networks as one of the dominant technology trends in the coming decades has posed numerous unique challenges on their security to researchers. These networks are likely to be composed of thousands of tiny sensor nodes, which are low-cost devices equipped with limited memory, processing, radio, and in many cases, without access to renewable energy resources. While the set of challenges in sensor networks are diverse, we focus on security of Wireless Sensor Network in this paper. First, we propose some of the security goal for Wireless Sensor Network. To perform any task in WSN, the goal is to ensure the best possible utilization of sensor resources so that the network could be kept functional as long as possible. In contrast to this crucial objective of sensor network management, a Denial of Service (DoS) attack targets to degrade the efficient use of network resources and disrupts the essential services in the network. DoS attack could be considered as one of th

scholarly journals A Lightweight Intrusion Detection Method Based on Fuzzy Clustering Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongchun Qu ◽  
Libiao Lei ◽  
Xiaoming Tang ◽  
Ping Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Detection Method ◽  
Base Station ◽  
Simulation Software ◽  
Wireless Sensor ◽  
Sensor Monitoring

For resource-constrained wireless sensor networks (WSNs), designing a lightweight intrusion detection technology has been a hot and difficult issue. In this paper, we proposed a lightweight intrusion detection method that was able to directly map the network status into sensor monitoring data received by base station, so that base station can sense the abnormal changes in the network. Our method is highlighted by the fusion of fuzzy c-means algorithm, one-class SVM, and sliding window procedure to effectively differentiate network attacks from abnormal data. Finally, the proposed method was tested on the wireless sensor network simulation software EXata and in real applications. The results showed that the intrusion detection method in this paper could effectively identify whether the abnormal data came from a network attack or just a noise. In addition, extra energy consumption can be avoided in all sensor monitoring nodes of the sensor network where our method has been deployed.

Energy Efficient Image Compression and Transmission in WSN

2016 ◽  
pp. 67-78
Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Sensor Network ◽  
Image Data ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.

Computationally Efficient Cooperative Public Key Authentication Protocols in Ubiquitous Sensor Network

2011 ◽  
pp. 211-229
Author(s):  
Abedelaziz Mohaisen ◽  
Tamer AbuHmed ◽  
DaeHun Nyang
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Key Management ◽  
Sensor Nodes ◽  
Public Key ◽  
Wireless Sensor ◽  
Security Requirement ◽  
Computationally Efficient ◽  
Authentication Protocols ◽  
Public Keys

The use of public key algorithms to sensor networks brings all merits of these algorithms to such networks: nodes do not need to encounter each other in advance in order to be able to communicate securely. However, this will not be possible unless “good” key management primitives that guarantee the functionality of these algorithms in the wireless sensor networks are provided. Among these primitives is public key authentication: before sensor nodes can use public keys of other nodes in the network to encrypt traffic to them, they need to make sure that the key provided for a particular node is authentic. In the near past, several researchers have addressed the problem and proposed solutions for it as well. In this chapter we review these solutions. We further discuss a new scheme which uses collaboration among sensor nodes for public key authentication. Unlike the existing solutions for public key authentication in sensor network, which demand a fixed, yet high amount of resources, the discussed work is dynamic; it meets a desirable security requirement at a given overhead constraints that need to be provided. It is scalable where the accuracy of the authentication and level of security are merely dependent upon the desirable level of resource consumption that the network operator wants to put into the authentication operation.

scholarly journals Auto-Configuration in Wireless Sensor Networks: A Review

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4281
Author(s):  
Ngoc-Thanh Dinh ◽  
Younghan Kim
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Limited Resources ◽  
Comprehensive Review ◽  
Advantages And Disadvantages ◽  
Critical Issues

Wireless sensor network (WSN) studies have been carried out for multiple years. At this stage, many real WSNs have been deployed. Therefore, configuration and updating are critical issues. In this paper, we discuss the issues of configuring and updating a wireless sensor network (WSN). Due to a large number of sensor nodes, in addition to the limited resources of each node, manual configuring turns out to be impossible. Therefore, various auto-configuration approaches have been proposed to address the above challenges. In this survey, we present a comprehensive review of auto-configuration mechanisms with the taxonomy of classifications of the existing studies. For each category, we discuss and compare the advantages and disadvantages of related schemes. Lastly, future works are discussed for the remaining issues in this topic.

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