Energy aware detection and prevention of black hole  attack in MANET

Panda, Niranjan; Pattanayak, Binod Kumar

doi:10.14419/ijet.v7i2.6.10139

Cited by 17 publications

(14 citation statements)

References 15 publications

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“…This characteristic of the network let to implement a trust model for co-relating with the innate trust being shared between the nodes. Energy-aware detection algorithms detect the black hole attack with enhanced security [3]. There is already enough research regarding black hole attack using AODV protocol [4,5].…”

Section: Literature Surveymentioning

confidence: 99%

Trust Management Based Improved Mechanism to Prevent MANET from Security Threats using Optimized SVM

Walia¹,

Malhotra²

2019

IJITEE

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A temporal network creates various issues which are managed by nodes, communicating with the base station. The flow of packets with different routes usually attacked by malicious nodes, such an attack is also termed as black hole attack. A novel FSAODV mechanism is proposed in this paper to prevent the information from malicious nodes by following the Ad-hoc on demand distance vector (AODV) protocol. The detection of threats due to the black hole and route enhancement is implemented using the bio-inspired algorithms. Firefly algorithm and Support Vector Machine (SVM) algorithms are developed to determine the throughput, Packet Delivery Ratio (PDR), and TDR. A comparative analysis has been done to portray the success rate of proposed work. For the comparison, research works of Ashok Koujalagi and Rushdi A. Hamamreh are considered. 33.33% enhancement has been noted in throughput with Ashok Koujalagi and74.44% with Rushdi A. Hamamreh. 21.4% enhancement has been seen in PDR with Ashok Koujalagi and 91.71% with Rushdi A. Hamamreh.

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Section: Literature Surveymentioning

confidence: 99%

Trust Management Based Improved Mechanism to Prevent MANET from Security Threats using Optimized SVM

Walia¹,

Malhotra²

2019

IJITEE

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“…The above-mentioned existing works have focused on only for the detection of Blackhole attack node. Panda et al [10] have worked for the detection as well as to minimize the side effect of the gray hole and Blackhole attack in MANET by implementing a new technique named as Ant Colony Optimization (ACO). The purpose of this technique is to determine the shortest route from transmitting node to the target node based on the energy consumption rate.…”

Section: Related Workmentioning

confidence: 99%

Mitigation of Blackhole Attack on MANETs using ABC and ANN Algorithm

Kharyal¹,

Krishna²

2019

IJITEE

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Mobile ad hoc network (MANET) is an important field of research that comprises of moveable nodes. These nodes communicate with each other through wireless links. Therefore, it becomes essential to design a secure network as it finds applications in different fields where data and communication are important like that in defense areas and disaster rescue operations. This paper focuses on detecting Blackhole nodes in MANETs and preventing it from the same. In this work, Ad hoc On-Demand Distance Vector (AODV) is employed as a routing mechanism and a secure network is established using Artificial Bee Colony (ABC) algorithm as an optimization technique in combination with Artificial Neural Network (ANN) as a classification algorithm to identify the Blackhole nodes. Simulations are carried out in MATLAB and the efficiency of the network in terms of Throughput, Packet Delivery Ratio (PDR), End-to-End Delay and Energy Consumption are measured. Throughput and PDR have been increased by 11.11%, 4.9 %, whereas end- to- end delay has been reduced by 4.93% as compared to existing work proposed by Ashish et al.[6].

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“…Selectively this attack can drop routing packets for a specific node or a portion of packets. In details a black-hole [11] is a malicious node as depicted in Figure. 7, which replies the Route Request (RREQ) in fake without having any route towords the desination and drops all the packets.…”

Section: Blackhole Attackmentioning

confidence: 99%

“…Grey-hole [11] attack is special case of black-hole attack in which an attacker becomes the part of an active route within the network as in black-hole attack but does not drop the data packets routed through it entirely. Initially attacker node may behave as legitimate node to trust but later on drop packets selectively with certain probability from some specific nodes or in some other specific pattern.…”

Section: Gray-hole Attackmentioning

confidence: 99%

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Defense Against Co-Operative Black-hole Attack and Gray-hole Attack in MANET

Panda¹,

Pattanayak²

2018

IJET

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Mobile Ad-hoc networks (MANETs) can be termed as an autonomous system created by the collaboration of a set of motile nodes communicating with one another through available wireless media and each node behaves as an end system, as well as a router for packet forwarding. Each node is allowed to move freely, change locations and configure them to form a network. Finding an optimal and efficient path between the sender and receiver node is the main aim of routing protocols. Multipath routing protocols show a better result in comparison to single path routing protocols, for data transmission from source to destination extending lifetime of the network. Along with that security in routing for a protected communication between nodes has become a prime concern as any attack during routing may interrupt data transmission, paralyzing the whole network. During packet transmission through multiple paths a number of attacks make come into action by the unauthenticated and compromised nodes present within the network and black-hole attack is one of them. So our objective is to design a multipath routing protocol that detects and avoids the path containing black-hole. Our paper proposes a way to defense the black-hole and gray-hole attacks with the help of intelligence in MANET.

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Energy aware detection and prevention of black hole attack in MANET

Cited by 17 publications

References 15 publications

Trust Management Based Improved Mechanism to Prevent MANET from Security Threats using Optimized SVM

Trust Management Based Improved Mechanism to Prevent MANET from Security Threats using Optimized SVM

Mitigation of Blackhole Attack on MANETs using ABC and ANN Algorithm

Defense Against Co-Operative Black-hole Attack and Gray-hole Attack in MANET

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