Multi-Node Data Security Detection Method for Stratified Heterogeneous Ocean Sensor Networks

2020 ◽  
Vol 115 (sp1) ◽  
pp. 238
Author(s):  
Ming Sun ◽  
Ruibin Niu
Information ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 236 ◽  
Author(s):  
Nengsong Peng ◽  
Weiwei Zhang ◽  
Hongfei Ling ◽  
Yuzhao Zhang ◽  
Lixin Zheng

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%.


2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongchun Qu ◽  
Libiao Lei ◽  
Xiaoming Tang ◽  
Ping Wang

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.


Author(s):  
Murat Al ◽  
Kenji Yoshigoe

Understanding data security is crucial to the daily operation of Wireless Sensor Networks (WSNs) as well as to the further advancement of security solutions in the research community. Unlike many surveys in literature that handle the topic in close relationship to a particular communication protocol, we provide a general view of vulnerabilities, attacks, and countermeasures in WSNs, enabling a broader audience to benefit from the presented material. We compare salient characteristics and applications of common wireless technologies to those of WSNs. As the main focus of the chapter, we thoroughly describe the characteristics of attacks and their countermeasures in WSNs. In addition, we qualitatively illustrate the multi-dimensional relationship among various properties including the effectiveness of these attacks (i.e., caused damage), the resources needed by adversaries to accomplish their intended attacks (i.e., consumed energy and time), and the resources required to defend against these attacks (i.e., energy overhead).


2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092577 ◽  
Author(s):  
Shahwar Ali ◽  
A Humaria ◽  
M Sher Ramzan ◽  
Imran Khan ◽  
Syed M Saqlain ◽  
...  

In wireless sensor networks, the sensors transfer data through radio signals to a remote base station. Sensor nodes are used to sense environmental conditions such as temperature, strain, humidity, sound, vibration, and position. Data security is a major issue in wireless sensor networks since data travel over the naturally exposed wireless channel where malicious attackers may get access to critical information. The sensors in wireless sensor networks are resource-constrained devices whereas the existing data security approaches have complex security mechanisms with high computational and response times affecting the network lifetime. Furthermore, existing systems, such as secure efficient encryption algorithm, use the Diffie–Hellman approach for key generation and exchange; however, Diffie–Hellman is highly vulnerable to the man-in-the-middle attack. This article introduces a data security approach with less computational and response times based on a modified version of Diffie–Hellman. The Diffie–Hellman has been modified to secure it against attacks by generating a hash of each value that is transmitted over the network. The proposed approach has been analyzed for security against various attacks. Furthermore, it has also been analyzed in terms of encryption/decryption time, computation time, and key generation time for different sizes of data. The comparative analysis with the existing approaches shows that the proposed approach performs better in most of the cases.


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