scholarly journals Accurate detection of selective forwarding attack in wireless sensor networks

2019 ◽  
Vol 15 (1) ◽  
pp. 155014771882400
Author(s):  
Qiong Zhang ◽  
Wenzheng Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Performance ◽  
Signal To Noise Ratio ◽  
Energy Resource ◽  
Attack Detection ◽  
Wireless Sensor ◽  
Detection Accuracy ◽  
Wireless Devices ◽  
Selective Forwarding

Selective forwarding attack in wireless sensor networks shows great impact on network performance and consumes limited energy resource. In previous countermeasures, it is assumed that all nodes in the communication range can detect misbehaviors of the attacker. However, as wireless devices require certain signal-to-noise ratio to receive frames correctly, and interference among nodes is inevitable in densely deployed wireless sensor networks, it is very difficult for previous approaches to detect misbehaviors accurately. In this article, a scheme named E-watchdog is proposed to improve accuracy of selective forwarding attack detection. Detection agents that are closer to the attacker are used to detect misbehaviors, which can improve the detection accuracy and reduce the false alarm rate effectively. Moreover, to prevent collaborative selective forwarding attack, E-watchdog uses reports from more than one detection agents. Fake reports from attackers are filtered out through an election algorithm. Simulation results show that the E-watchdog reduces the false detection rate by 25% and improves the detection accuracy by 10% on the premise of increasing negligible energy consumption.

Intermittent Faults Diagnosis in Wireless Sensor Networks

2012 ◽  
Vol 160 ◽  
pp. 318-322
Author(s):  
Yin Qiu Sun ◽  
Hai Lin Feng
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Performance ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Detection Accuracy ◽  
Distributed Clustering ◽  
Intermittent Faults ◽  
Diagnosis Method ◽  
Faults Diagnosis

Sensor node intermittent faults which sometimes behave as fault-free are common in wireless sensor networks. Intermittent faults also affect network performance and faults detection accuracy, so it is important to diagnose the intermittent faulty nodes accurately. This paper proposes a distributed clustering intermittent faults diagnosis method. First, the network is divided into several clusters with the cluster heads should be diagnosed as good. Then, the cluster members are diagnosed by their cluster head. In order to improve the validity of proposed diagnose method, a strategy which collect data for many times is adopted. Analysis of fault diagnosable is given, and simulation results indicate the proposed algorithm has high fault detection accuracy.

scholarly journals A SOLUTION TO SELECTIVE FORWARD ATTACK IN WIRELESS SENSOR NETWORK

2018 ◽  
Vol 6 (2) ◽  
pp. 25-30 ◽  
Author(s):  
Gulbir Singh ◽  
Om Prakash Dubey ◽  
Gautam Kumar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Packet Loss ◽  
Network Performance ◽  
Mesh Network ◽  
Wireless Sensor ◽  
Sybil Attack ◽  
Trust Value ◽  
Selective Forwarding ◽  
The Many

Wireless mesh network represent a solution to provide wireless connectivity. There is some attacks on wireless sensor networks like black hole attack, sinkhole attack, Sybil attack, selective forwarding, etc. In this paper, we will concentrate on selective forwarding attack. Selective Forwarding Attack is one of the many security threats in wireless sensor networks which can degrade network performance. An adversary on the transmission path selectively drops the packet. The adversary same time transfers the packet, while in a few occasions it drops the packet. It is difficult to detect this type of attack since the packet loss may be due to unreliable wireless communication. The proposed scheme is based on the trust value of each node. During data transmission, a node selects a downstream node that has highest trust value, which is updated dynamically based on the number of packets a node has forwarded and dropped. We compared our scheme with the existing scheme and found that the packet loss in the proposed scheme is much less than the existing scheme.

scholarly journals Detection of selective forwarding attacks based on adaptive learning automata and communication quality in wireless sensor networks

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881504 ◽  
Author(s):  
Hongliang Zhu ◽  
Zhihua Zhang ◽  
Juan Du ◽  
Shoushan Luo ◽  
Yang Xin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Adaptive Learning ◽  
Packet Loss ◽  
Learning Automata ◽  
Attack Detection ◽  
Wireless Sensor ◽  
Communication Quality ◽  
Selective Forwarding

Wireless sensor networks face threats of selective forwarding attacks which are simple to implement but difficult to detect. It is difficult to distinguish between malicious packet dropping and the normal packet loss on unstable wireless channels. For this situation, a selective forwarding attack detection method is proposed based on adaptive learning automata and communication quality; the method can eliminate the impact of normal packet loss on selective forwarding attack detection and can detect ordinary selective forwarding attack and special cases of selective forwarding attack. The current and comprehensive communication quality of nodes are employed to reflect the short- and long-term forwarding behaviors of nodes, and the normal packet loss caused by unstable channels and medium-access-control layer collisions is considered. The adaptive reward and penalty parameters of a detection learning automata are determined by the comprehensive communication quality of the node and the voting of its neighbors to reward normal nodes or punish malicious ones. Simulation results indicate the effectiveness of the proposed method in detecting ordinary selective forwarding attacks, black-hole attacks, on-off attacks, and energy exhaustion attacks. In addition, the communication overhead of the method is lower than that of other methods.

Research on Selective Forwarding Attack Detection Scheme in Wireless Sensor Networks

2012 ◽  
Vol 433-440 ◽  
pp. 5298-5302
Author(s):  
Ying Wang ◽  
Guo Rui Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Attack Detection ◽  
Wireless Sensor ◽  
Detection Scheme ◽  
Selective Forwarding ◽  
Critical Facilities ◽  
Mission Critical ◽  
Detection Schemes ◽  
Lower False Alarm Rate

Selective forwarding attacks in wireless sensor networks may corrupt some mission critical applications such as military surveillance and critical facilities monitoring. They are very difficult to be detected and distinguished from normal packet drops in wireless sensor networks. We propose an improved sequential mesh test based detection scheme in this paper. The scheme extracts a small quantity of samples to run the test, instead of regulating the total times of test in advance. We show through experiments that our scheme can provide higher detection accurate rate and lower false alarm rate than the existing detection schemes. Meanwhile, less communication and computation power are required to detect the selective forwarding attacks.

Sign in / Sign up

Export Citation Format

Share Document