scholarly journals Malicious Detection using Secure Mutual Trust Based Routing on an Intrusion Detection System in WSN

2019 ◽  
Vol 8 (3) ◽  
pp. 3144-3150
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Trust Management ◽  
Detection System ◽  
Trust Model ◽  
The Other ◽  
Sensor Nodes ◽  
Mutual Trust ◽  
Malicious Nodes ◽  
Routing Methods

The Lack of infrastructure makes secured data distribution, challenging task in Wireless Sensor Networks (WSNs). In traditional routing methods, either security or routing optimization is addressed separately; however, both are not addressed at similar instances. Hence, if there exists a bottleneck while handling security or routing, where either one is affected by the other. In this paper, Mutual Trust Management (MTM) framework is designed between the sensor nodes is proposed in WSN to identify the malicious nodes. The trust model is connected with an Intrusion Detection System (IDS) to effectively analyse the malicious nodes and routing of packets between the nodes is designed with the Structure of a Multilayer Perceptron (MLP) Network to route the packets through the secured path. The simulations are conducted using the NS-2 setup for validating the trustworthiness and packet delivery through the secured route. The proposed method is compared against the existing methods to test the efficacy of MTM-MLP model and the results show that the MTM-MLP achieves higher detection against ransomware than the other methodsThe Lack of infrastructure makes secured data distribution, challenging task in Wireless Sensor Networks (WSNs). In traditional routing methods, either security or routing optimization is addressed separately; however, both are not addressed at similar instances. Hence, if there exists a bottleneck while handling security or routing, where either one is affected by the other. In this paper, Mutual Trust Management (MTM) framework is designed between the sensor nodes is proposed in WSN to identify the malicious nodes. The trust model is connected with an Intrusion Detection System (IDS) to effectively analyse the malicious nodes and routing of packets between the nodes is designed with the Structure of a Multilayer Perceptron (MLP) Network to route the packets through the secured path. The simulations are conducted using the NS-2 setup for validating the trustworthiness and packet delivery through the secured route. The proposed method is compared against the existing methods to test the efficacy of MTM-MLP model and the results show that the MTM-MLP achieves higher detection against ransomware than the other methods

Weighted K Nearest Neighbour-Based Cooperation Intrusion Detection System for Wireless Sensor Networks

2012 ◽  
Vol 263-266 ◽  
pp. 2972-2978
Author(s):  
Ju Long Pan ◽  
Ling Long Hu ◽  
Wen Jin Li ◽  
Hui Cui ◽  
Zi Yin Li
Keyword(s):  
Wireless Sensor Networks ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection Rate ◽  
Detection System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nearest Neighbour ◽  
Malicious Nodes ◽  
Detection Scheme

To identify the malicious nodes timely in wireless sensor networks(WSNs), a cooperation intrusion detection scheme based on weighted k Nearest Neighbour(kNN) is proposed. Given a few types of sensor nodes, the test model extracts the properties of sensor nodes related with the known types of malicious nodes, and establishes sample spaces of all sensor nodes which participate in network activities. According to the known node’s attributes sampled, the unknown type sensor nodes are classified based on weighted kNN. Considering of energy consumption, an intrusion detection system selection algorithm is joined in the sink node. Simulation results show that the scheme has a lower false detection rate and a higher detection rate at the same time, and it can preserve energy of detection nodes compared with an existing intrusion detection scheme.

scholarly journals A New Neural Network-Based Intrusion Detection System for Detecting Malicious Nodes in WSNs

2020 ◽  
Vol 1 (3) ◽  
pp. 1-8
Author(s):  
Narmatha C ◽  
Keyword(s):  
Neural Network ◽  
Intrusion Detection ◽  
Key Management ◽  
Intrusion Detection System ◽  
Detection System ◽  
Denial Of Service ◽  
Fuzzy Rule ◽  
Sensor Nodes ◽  
Abnormal Behavior ◽  
Malicious Nodes

The Wireless Sensor Networks (WSNs) are vulnerable to numerous security hazards that could affect the entire network performance, which could lead to catastrophic problems such as a denial of service attacks (DoS). The WSNs cannot protect these types of attacks by key management protocols, authentication protocols, and protected routing. A solution to this issue is the intrusion detection system (IDS). It evaluates the network with adequate data obtained and detects the sensor node(s) abnormal behavior. For this work, it is proposed to use the intrusion detection system (IDS), which recognizes automated attacks by WSNs. This IDS uses an improved LEACH protocol cluster-based architecture designed to reduce the energy consumption of the sensor nodes. In combination with the Multilayer Perceptron Neural Network, which includes the Feed Forward Neutral Network (FFNN) and the Backpropagation Neural Network (BPNN), IDS is based on fuzzy rule-set anomaly and abuse detection based learning methods based on the fugitive logic sensor to monitor hello, wormhole and SYBIL attacks.

scholarly journals A Hybrid Intrusion Detection System for IoT Applications with Constrained Resources

2020 ◽  
Vol 12 (1) ◽  
pp. 109-130 ◽  
Author(s):  
Chao Wu ◽  
Yuan'an Liu ◽  
Fan Wu ◽  
Feng Liu ◽  
Hui Lu ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Resource Constraints ◽  
Detection System ◽  
Data Gathering ◽  
Malicious Nodes ◽  
Network Information ◽  
Malicious Node Detection ◽  
The Impact ◽  
Cyber Criminals

Network security and network forensics technologies for the Internet of Things (IoT) need special consideration due to resource-constraints. Cybercrimes conducted in IoT focus on network information and energy sources. Graph theory is adopted to analyze the IoT network and a hybrid Intrusion Detection System (IDS) is proposed. The hybrid IDS consists of Centralized and Active Malicious Node Detection (CAMD) and Distributed and Passive EEA (Energy Exhaustion Attack) Resistance (DPER). CAMD is integrated in the genetic algorithm-based data gathering scheme. CAMD detects malicious nodes manipulated by cyber criminals and provides digital evidence for forensics. DPER is implemented in a set of communication protocols to alleviate the impact of EEA attacks. Simulation experiments conducted on NS-3 platform showed the hybrid IDS proposed detected and traced malicious nodes precisely without compromising energy efficiency. Besides, the impact of EEA attacks conducted by cyber criminals was effectively alleviated.

scholarly journals PDTB-IDS: A Parameter and Distributed Trust Based Intrusion Detection System for Wireless Sensor Network

2019 ◽  
Vol 8 (4) ◽  
pp. 11730-11737
Keyword(s):  
Wireless Sensor Network ◽  
Intrusion Detection ◽  
Sensor Network ◽  
Intrusion Detection System ◽  
Detection System ◽  
Research Work ◽  
Trust Model ◽  
Secure Routing ◽  
Wireless Sensor ◽  
General Trust

Wireless sensor network (WSN) is a noteworthy division in present day correspondence frameworks and faith detecting steering convention is utilized to improve security in WSN. Already, Trust Sensing based Secure Routing Mechanism (TSSRM) was projected which will diminish the overhead steering and improve the unwavering quality of information transmission over the system. In any case, the security tool of this technique might be invalid, if the system steering convention is modified. Hence, in this work, a Parameter and Distributed Trust Based Intrusion Detection System (PDTB-IDS) with a safe correspondence structure with a trust the board framework for remote sensor systems are proposed. The significant commitment is to distinguish different parameters and trust factors that impact trust in WSN is conveyed among different factors, for example, vitality, unwavering quality, information, and so on. Subsequently coordinate believe, proposal believe and circuit trust from those components are determined and the general trust estimation of the sensor hub is evaluated by joining the individual trust esteems. The trust model can decide whether or not the specific hub is pernicious or not by looking at trust got from the proposed method. The numerical assessment of the research work is completed with the help of NS2 simulation environment from which it is proved that the projected strategy provides enhanced outcome than the present TSSRM method.

scholarly journals A Dual Attack Detection Technique to Identify Black and Gray Hole Attacks Using an Intrusion Detection System and a Connected Dominating Set in MANETs

2019 ◽  
Vol 11 (3) ◽  
pp. 61 ◽  
Author(s):  
Zulfiqar Ali Zardari ◽  
Jingsha He ◽  
Nafei Zhu ◽  
Khalid Mohammadani ◽  
Muhammad Pathan ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Ad Hoc ◽  
Detection System ◽  
Dominating Set ◽  
Attack Detection ◽  
Connected Dominating Set ◽  
Malicious Nodes ◽  
Mobile Ad Hoc ◽  
Behavioral Information

A mobile ad-hoc network (MANET) is a temporary network of wireless mobile nodes. In a MANET, it is assumed that all of the nodes cooperate with each other to transfer data packets in a multi-hop fashion. However, some malicious nodes don’t cooperate with other nodes and disturb the network through false routing information. In this paper, we propose a prominent technique, called dual attack detection for black and gray hole attacks (DDBG), for MANETs. The proposed DDBG technique selects the intrusion detection system (IDS) node using the connected dominating set (CDS) technique with two additional features; the energy and its nonexistence in the blacklist are also checked before putting the nodes into the IDS set. The CDS is an effective, distinguished, and localized approach for detecting nearly-connected dominating sets of nodes in a small range in mobile ad hoc networks. The selected IDS nodes broadcast a kind of status packet within a size of the dominating set for retrieving the complete behavioral information from their nodes. Later, IDS nodes use our DDBG technique to analyze the collected behavioral information to detect the malicious nodes and add them to the blacklist if the behavior of the node is suspicious. Our experimental results show that the quality of the service parameters of the proposed technique outperforms the existing routing schemes.

Hybrid Intrusion Detection Framework for Ad Hoc Networks

2020 ◽  
pp. 1312-1346
Author(s):  
Abdelaziz Amara Korba ◽  
Mehdi Nafaa ◽  
Salim Ghanemi
Keyword(s):  
Intrusion Detection ◽  
Anomaly Detection ◽  
Ad Hoc Networks ◽  
Intrusion Detection System ◽  
Ad Hoc ◽  
Detection System ◽  
Hierarchical Architecture ◽  
Security Framework ◽  
Malicious Nodes ◽  
Hoc Networks

In this paper, a cluster-based hybrid security framework called HSFA for ad hoc networks is proposed and evaluated. The proposed security framework combines both specification and anomaly detection techniques to efficiently detect and prevent wide range of routing attacks. In the proposed hierarchical architecture, cluster nodes run a host specification-based intrusion detection system to detect specification violations attacks such as fabrication, replay, etc. While the cluster heads run an anomaly-based intrusion detection system to detect wormhole and rushing attacks. The proposed specification-based detection approach relies on a set of specifications automatically generated, while anomaly-detection uses statistical techniques. The proposed security framework provides an adaptive response against attacks to prevent damage to the network. The security framework is evaluated by simulation in presence of malicious nodes that can launch different attacks. Simulation results show that the proposed hybrid security framework performs significantly better than other existing mechanisms.

scholarly journals Intrusion Detection Algorithm Based on Change Rates of Multiple Attributes for WSN

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Hongying Bai ◽  
Xiaotong Zhang ◽  
Fangjie Liu
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Great Influence ◽  
Detection Algorithm ◽  
Sensor Nodes ◽  
True Positive ◽  
Change Rate ◽  
Fast Convergence Rate ◽  
Multiple Attributes

Intrusion detection system (IDS) is a second line of the security mechanism for the wireless sensor network (WSN), and it has a great influence on confidentiality, integrity, and availability. However, many existing IDS only detect single attack or multiple known attacks. In this paper, a novel intrusion detection algorithm based on change rates of multiple attributes (CRMA) is proposed, which can detect multiple attacks including known and unknown types simultaneously. The change rates of multiple attributes for sensor nodes usually reflect the running states of WSN over a period of time. First, the Observed Change Rate of attributes at different times is obtained by observing multiple attributes of different sensor nodes. Then, the convex optimization is alternately used to obtain the Normal Change Rate and corresponding weights by minimizing the distance between the Observed Change Rate and the Normal Change Rate of each attribute. Finally, the WSN is considered to be attacked when the weighted deviation of the Observed Change Rate and Normal Change Rate is beyond the corresponding threshold. Experimental results show that the CRMA can detect multiple attacks including known and unknown types simultaneously and has a fast convergence rate. The average true positive rates (TPR) of CRMA are high, and the average false positive rates (FPR) of CRMA are low. The detection performance of CRMA is superior to that of the ARMA and NeTMids algorithms.

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