CREDND: A Novel Secure Neighbor Discovery Algorithm for Wormhole Attack

Luo, Xiwen; Chen, Yanru; Li, Miao; Luo, Qian; Xue, Kang; Liu, Shijia; Chen, Liangyin

doi:10.1109/access.2019.2894637

Cited by 36 publications

(43 citation statements)

References 47 publications

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“…Here, two situations are implemented and looked at. In the first situation, existing strategy that is CREDND [12] for the identification of malevolent is implemented, which likewise utilizes hop distinction and neighborhood checking to spot wormholes. In the proposed outline, the two-phase verification scheme is implemented for the recognition of malevolent nodes in the system, E-CREDND.…”

Section: Resultsmentioning

confidence: 99%

“…We propose E-CREDND, a novel calculation for wormhole identification and confinement, which can identify wormholes without extra equipment. We test the correctness of our novel calculation by reenacting and contrasting it and other wormhole identification calculation: CREDND [12], who likewise utilizes hop distinction and neighborhood checking. The results prove that our method outclasses existing method.…”

Section: Eai Endorsed Transactions On Mobile Communications and Applimentioning

confidence: 99%

“…The anticipated calculation is basic, localized convention and does not need any extraordinary equipment, localization or synchronization. [12] have considered wormhole recognition under nondeterministic arrangement and furthermore anticipated the idea of neighbor ratio threshold to figure out which all nodes should be distinguished, which adds to improving the precision and vitality productivity of wormhole location. However, this arrangement can't function admirably in the state that all nodes with various correspondence ranges, progressively changing and adjusting to different circulations.…”

Section: Related Workmentioning

confidence: 99%

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E-CREDND Scheme for Detection of malevolent nodes in Ad-hoc Network

Shilpi¹,

Rizvi²

2018

ICST Transactions on Mobile Communications and Applications

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The remote network that comprises of multipurpose nodes and is infrastructure-less in nature is mobile ad-hoc network (MANET). It powerfully self-composes in subjective and impermanent system topologies. These moveable ad-hoc systems are dishonest and powerless to any interruption in light of their remote association approach. Subsequently, the data from these systems can be stolen effectively just by presenting the aggressor nodes in the system. The hop count metric is calculated to determine the straight route degree. For this reason, directing conventions are arranged. Among all the potential assaults on MANET, identification of wormhole attack is considered to be most problematic. One malevolent node gets packets from a specific area, tunnels them to an alternate transmissible node arranged in another area of the system and deforms the full steering strategy. All routes are merged to the wormhole set up by the aggressors. The total directing framework in MANET gets diverted. Here in this paper, a procedure for identifying malevolent nodes in movable ad-hoc system has been proposed (E-CREDND) and this scheme is critical for the regions where the route separate in the midst of source and goal is two nodes only. This scheme isn't appropriate for those situations where multi-hops are exhibited in the midst of transmitter and recipient. In the anticipated investigation, another procedure is executed for the identification and separation of aggressor sensor nodes from the system. The anticipated plan is used in NS2 and it is portrayed by the propagation results that the anticipated plan demonstrates better execution in correlation with existing methodologies.

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Section: Resultsmentioning

confidence: 99%

Section: Eai Endorsed Transactions On Mobile Communications and Applimentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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E-CREDND Scheme for Detection of malevolent nodes in Ad-hoc Network

Shilpi¹,

Rizvi²

2018

ICST Transactions on Mobile Communications and Applications

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“…The True-Positive and False-Positive detection rates of the wormhole attack are compared with results obtained by recent research work done by Xiao Luo et al [50]. By considering attacker nodes, 10% of total nodes, the reading for all methods are taken as per Table 4 and Table 5.…”

Section: Performance Analysis Of Implemented System 431 Attack Detementioning

confidence: 99%

Wormhole Attack Detection System for IoT Network: A Hybrid Approach

Bhosale¹,

Sonavane

2021

Preprint

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Many errors in data communication cause security attacks in Internet of Things (IoT). Routing errors which are prominent errors in IoT, degrade the quality of data communication. Many attacks like sinkhole attack, blackhole attack, selective forwarding attack and wormhole attack enter the network through network layer of the IoT. This paper has an emphasis on the wormhole attack detection because it is one of the most uncompromising attacks at the network layer of IoT protocol stack. The wormhole attack inserts wrong routes information in the network; it also alters the network information by causing failure of the location-dependent protocols thus defeating the purpose of routing algorithms. The wormhole attack is activated in the network by forming a tunnel between two long-distance nodes. These nodes create an illusion that they are directly connected and nearer to each other. They attract legitimate nodes to transmit data through them by advertising less hop-count. Most of the time, due to the presence of attack, packets take the long route and reduce their strength. This paper covers the design and implementation of an innovative intrusion detection system for the IoT that detects the wormhole attack and the attacker nodes. The presence of the wormhole attack is identified using location information of any node and its neighbor with the help of Received Signal Strength Indicator (RSSI) values and hop-count. The proposed system is energy efficient and hence it is beneficial for a resource-constrained environment of IoT. It also provides precise true-positive and false-positive detection rate.

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“…Generally, WSN is vulnerable to various kinds of threats [9][10][11]. The several attacks in WSN are Sybil attacks, wormhole attacks, black hole attacks, and hello flood attacks [12,13]. The WSN has some security goals such as primary and secondary.…”

Section: Introductionmentioning

confidence: 99%

A GOA Based Secure Routing Algorithm for Improving Packet Delivery and Energy Efficiency in Wireless Sensor Networks

2021

IJIES

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CREDND: A Novel Secure Neighbor Discovery Algorithm for Wormhole Attack

Cited by 36 publications

References 47 publications

E-CREDND Scheme for Detection of malevolent nodes in Ad-hoc Network

E-CREDND Scheme for Detection of malevolent nodes in Ad-hoc Network

Wormhole Attack Detection System for IoT Network: A Hybrid Approach

A GOA Based Secure Routing Algorithm for Improving Packet Delivery and Energy Efficiency in Wireless Sensor Networks

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