scholarly journals A Novel Low-Rate Denial of Service Attack Detection Approach in ZigBee Wireless Sensor Network by Combining Hilbert-Huang Transformation and Trust Evaluation

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 32853-32866 ◽  
Author(s):  
Hongsong Chen ◽  
Caixia Meng ◽  
Zhiguang Shan ◽  
Zhongchuan Fu ◽  
Bharat K. Bhargava
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Denial Of Service ◽  
Attack Detection ◽  
Wireless Sensor ◽  
Trust Evaluation ◽  
Denial Of Service Attack ◽  
Detection Approach ◽  
Service Attack ◽  
Low Rate

Low rate TCP denial-of-service attack detection at edge routers

2005 ◽  
Vol 9 (4) ◽  
pp. 363-365 ◽  
Author(s):  
A. Shevtekar ◽  
K. Anantharam ◽  
N. Ansari
Keyword(s):  
Denial Of Service ◽  
Attack Detection ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Low Rate

Modeling and Simulation of Low Rate of Denial of Service Attacks

2014 ◽  
Vol 484-485 ◽  
pp. 1063-1066
Author(s):  
Kui Liang Xia
Keyword(s):  
High Efficiency ◽  
Denial Of Service ◽  
Research Work ◽  
Attack Detection ◽  
Detection Methods ◽  
Dos Attacks ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
User Data ◽  
Low Rate

The low-rate denial of service attack is more applicable to the network in recent years as a means of attack, which is different from the traditional field type DoS attacks at the network end system or network using adaptive mechanisms exist loopholes flow through the low-rate periodic attacks on the implementation of high-efficiency attacked by an intruder and not be found, resulting in loss of user data or a computer deadlock. LDos attack since there has been extensive attention of researchers, the attack signature analysis and detection methods to prevent network security have become an important research topic. Some have been proposed for the current attacks were classified LDoS describe and model, and then in NS-2 platform for experimental verification, and then LDoS attack detection to prevent difficulties are discussed and summarized for the future such attacks detection method research work to provide a reference.

UWDBCSN Analysis During Node Replication Attack in WSN

2021 ◽  
pp. 634-650
Author(s):  
Harpreet Kaur ◽  
Sharad Saxena
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Weather Forecast ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Clustering ◽  
Wormhole Attack ◽  
Denial Of Service Attack ◽  
Service Attack

Wireless sensor network is an emerging area in which multiple sensor nodes are present to perform many real-time applications like military application, industrialized automation, health monitoring, weather forecast, etc. Sensor nodes can be organized into a group which is led by a cluster head; this concept is known as clustering. Clustering of wireless sensor network is used when sensor nodes want to communicate simultaneously in a single network. The author organizes the sensor nodes by applying UWDBCSN (underwater density-based clustering sensor network) clustering approach in which routing of the packets is controlled by cluster head. The author also considers the security of sensor nodes which are harmful to different types of mischievous attacks like wormhole attack, denial of service attack, replication or cloning attack, blackhole attack, etc. Node replication is one of the types in which an attacker tries to capture the node and generate the replica or clone of that node in the same network. So, this chapter describes how to deal with these types of attacks. The author used the intrusion detection process to deal with this type of attack. All the detection procedure is combined with sleep/wake scheduling algorithm to increase the performance of sensor nodes in the network.

UWDBCSN Analysis During Node Replication Attack in WSN

2018 ◽  
pp. 210-227 ◽  
Author(s):  
Harpreet Kaur ◽  
Sharad Saxena
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Weather Forecast ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Clustering ◽  
Wormhole Attack ◽  
Denial Of Service Attack ◽  
Service Attack

Wireless sensor network is an emerging area in which multiple sensor nodes are present to perform many real-time applications like military application, industrialized automation, health monitoring, weather forecast, etc. Sensor nodes can be organized into a group which is led by a cluster head; this concept is known as clustering. Clustering of wireless sensor network is used when sensor nodes want to communicate simultaneously in a single network. The author organizes the sensor nodes by applying UWDBCSN (underwater density-based clustering sensor network) clustering approach in which routing of the packets is controlled by cluster head. The author also considers the security of sensor nodes which are harmful to different types of mischievous attacks like wormhole attack, denial of service attack, replication or cloning attack, blackhole attack, etc. Node replication is one of the types in which an attacker tries to capture the node and generate the replica or clone of that node in the same network. So, this chapter describes how to deal with these types of attacks. The author used the intrusion detection process to deal with this type of attack. All the detection procedure is combined with sleep/wake scheduling algorithm to increase the performance of sensor nodes in the network.

Detection and Isolation Technique for Blackhole Attack in Wireless Sensor Network

2017 ◽  
Vol 7 (8) ◽  
pp. 25
Author(s):  
Mandeep Thakur ◽  
Amninder Kaur Gill
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Denial Of Service ◽  
Wireless Sensor ◽  
Malicious Nodes ◽  
Isolation Technique ◽  
Network Effectiveness ◽  
Denial Of Service Attack ◽  
Active Attacks ◽  
Novel Strategy

A wireless sensor network comprises of countless spread over a particular territory where we need to take care of at the progressions going ahead there. A sensor hub, for the most part, comprises of sensors, actuators, memory, a processor and they do have correspondence capacity. These sorts of networks are much powerless against security attacks. Many kinds of active and passive attacks are conceivable in the sensor network. Among all the conceivable active attacks, sinkhole attack is the most widely recognized and destructive attack. This attack debases network execution and prompts denial of service attack. The attack is triggered by the malicious hub which is available in the network. In this work, a novel strategy has been proposed to recognize and disengage malicious nodes from the network which are in charge of triggering the attack. The novel procedure is based on blacklist technique and clustering technique. The exploratory results will demonstrate that proposed strategy detects and separate the malicious nodes from the network proficiently. It will enhance network effectiveness as far as bundle misfortune, defer and expand throughput of the network. NS2 simulator instrument will be utilized as a part of it.

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