Ant based Defense Mechanism for Selective Forwarding Attack in MANET

Kumari, S. Vadhana; Paramasivan, B.

doi:10.1109/icdew.2015.7129553

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…The algorithm suffers from high routing overhead as each node sends an acknowledgment message to the prior node. In addition to the above problem, Kumari and Paramasivan [ 25 ] developed a routing mechanism of trust where the behavior of nodes is analyzed based on the dropping rate of packets, but this protocol also suffers from high overhead because of the additional use of control packets. Gurung and Chauhan [ 26 ] used the approach of mitigating a Gray Hole Attack (GHA) that takes the help of other nearby nodes, known as the nodes of the Intrusion Detection System (IDS), to monitor the performance of other communicating nodes.…”

Section: Related Workmentioning

confidence: 99%

“…The concept of SI is increasingly intertwined with algorithms for processing and optimizing the large amount and flows of information. In [ 25 ], a survey on different SI algorithms along with their role in the IoT is presented. The authors stated that SI in a wireless network can be used for Cluster Head (CH) selection, for sensor deployment, node localization, and in IoT to minimize the number of hops from the sensor node to the sink node.…”

Section: Introductionmentioning

confidence: 99%

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Robust and Secure Data Transmission Using Artificial Intelligence Techniques in Ad-Hoc Networks

Rani

Kavita

Verma

et al. 2021

Sensors

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The paper presents a new security aspect for a Mobile Ad-Hoc Network (MANET)-based IoT model using the concept of artificial intelligence. The Black Hole Attack (BHA) is considered one of the most affecting threats in the MANET in which the attacker node drops the entire data traffic and hence degrades the network performance. Therefore, it necessitates the designing of an algorithm that can protect the network from the BHA node. This article introduces Ad-hoc On-Demand Distance Vector (AODV), a new updated routing protocol that combines the advantages of the Artificial Bee Colony (ABC), Artificial Neural Network (ANN), and Support Vector Machine (SVM) techniques. The combination of the SVM with ANN is the novelty of the proposed model that helps to identify the attackers within the discovered route using the AODV routing mechanism. Here, the model is trained using ANN but the selection of training data is performed using the ABC fitness function followed by SVM. The role of ABC is to provide a better route for data transmission between the source and the destination node. The optimized route, suggested by ABC, is then passed to the SVM model along with the node’s properties. Based on those properties ANN decides whether the node is a normal or an attacker node. The simulation analysis performed in MATLAB shows that the proposed work exhibits an improvement in terms of Packet Delivery Ratio (PDR), throughput, and delay. To validate the system efficiency, a comparative analysis is performed against the existing approaches such as Decision Tree and Random Forest that indicate that the utilization of the SVM with ANN is a beneficial step regarding the detection of BHA attackers in the MANET-based IoT networks.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust and Secure Data Transmission Using Artificial Intelligence Techniques in Ad-Hoc Networks

Rani

Kavita

Verma

et al. 2021

Sensors

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“…In order to overcome with black hole attack problem, the authors proposed an enhanced Ant-based defense mechanism for selective forwarding attack [34] in MANET. In this mechanism, the trust model is used that defines the trustworthiness of the node based on the number of time the packet is dropped.…”

Section: Trust-based Schemesmentioning

confidence: 99%

A survey of black-hole attack mitigation techniques in MANET: merits, drawbacks, and suitability

Gurung

Chauhan

2019

Wireless Netw

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Mobile Ad-hoc Network (MANET) is a prominent technology in the wireless network in which the mobile nodes operate in a distributed manner and collaborate with each other in order to provide the multi-hop communication between the source and the destination node. Generally, the main assumption considered in the MANET is that each node is a trusted node. However, in a real scenario, there are some unreliable nodes which misbehave and launch the attack in network like blackhole in which the misbehaving nodes attract all the traffic towards itself by giving false information of having a shortest path towards the destination with a very high destination sequence number. In this paper, we discussed different possible nature of the nodes in the network that can lead to the different possible attacks. We have also presented the different classification of the techniques and discussed the merits, drawbacks, and suitability of the various techniques in different scenarios which need to be taken into consideration while designing an efficient protocol.

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