Analysis and Countermeasures of Black-Hole Attack in MANET by Employing Trust-Based Routing

Naveena, S.; Senthilkumar, C.; Manikandan, T.

doi:10.1109/icaccs48705.2020.9074282

Cited by 15 publications

(7 citation statements)

References 20 publications

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“…Naveena et al [15] suggested a trust-based routing scheme for secure routing. Two stages are used in this scheme, where the first type is data retrieval and the second stage is data transfer mechanism.…”

Section: Literature Reviewmentioning

confidence: 99%

Detection of Black Hole Attack Using Honeypot Agent-Based Scheme with Deep Learning Technique on MANET

Srinivasan¹

2021

ISI

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Mobile Ad-Hoc Networks (MANETs) due to their reconfigurable nature are being integrated into new and futuristic knowledge such as Internet of Things (IoT), cloud, reconfigurable networks, etc. To attain such credibility of integration, the routing protocols associated with these mobile nodes have to connect, perform and facilitate routing that offers a high level of security and resistance to all possible threats and security issues that may emanate in the network. One of the solutions used to maintain network security is intrusion detection systems (IDSs). This article primarily emphasis on the network's susceptibility to a suction assault known as a black hole attack. The investigations about the employment of intelligent agents called Honeypot Agent-based detection scheme (HPAS) with Long-Short Term Memory (LSTM) in identifying such assaults. Hence, the proposed method is named HPAS-LSTM, where honeypots are roaming virtual software managers that create Route Request (RREQ) packets to attract and entrap black hole attackers. Extensive model results utilizing the ns-2 simulator are used to demonstrate the presence of the suggested detection technique. The simulation outcomes demonstrate that the suggested technique outperforms current black hole detection methods in terms of throughput (TH), packet loss rate (PLR), packet delivery ratio (PDR), and total network delay (TND).

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Section: Literature Reviewmentioning

confidence: 99%

Detection of Black Hole Attack Using Honeypot Agent-Based Scheme with Deep Learning Technique on MANET

Srinivasan¹

2021

ISI

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“…This causes complicated nodes when a group of malicious nodes are acted together. To overcome these issues a novel system was introduced which effectively manage the effect of a joint grey-black hole attack [21]. Furthermore, it will be extended using conventional neural network (CNN) to predict the intruder with better accuracy.…”

Section: Black Holementioning

confidence: 99%

Host based Detection and Prevention of Black Hole attacks by AODV-ICCSO Algorithm for security in MANETs

Sathyaraj¹,

D²,

Kannan³

2021

Preprint

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Background: Mobile Ad-hoc Networks (i.e.) MANETs are gaining rapid fame in recent days and are considered as very significant because of their easier implementation and growing property. Various types of attacks are prone to damage the networks due to the elastic property possessed by the network. And among different categories of attacks that can affect MANETs, black hole attack is considered as the commonly occurring one within a MANET. Chicken Swarm Optimization (CSO) algorithm is one among the technique used for the detection of black hole attacks occurring in the MANETs. But the CSO algorithm possesses some disadvantages and necessity rises for overcoming the weakness in the CSO algorithm. Objective: Therefore, in this research paper, to address the black hole attack in MANET, an Improved Crossover Chicken Swarm Optimization (ICCSO) algorithm and the concept of Enhanced Partially-Mapped Crossover operation proposed and the best fitness values obtained. Methods: In ICCSO algorithm, parameter initialization is carried out in step 1 of the algorithm, where the attacked nodes and non-attack nodes are created separately with the aid of parameters like PDR (i.e.) Packet Delivery Ratio and RSSI (i.e.) Received Signal Strength Indicator. Further, If the node is affected by any attack, then the nodes are discarded and the data is transmitted through the non-attacked node. Routing is carried by a protocol of AODV.Results: The effectiveness of the algorithm proposed in the work is evaluated using various performance measures like packet delivery ratio (PDR), end-to-end delay (EED) and throughput. The performance measures are compared with a different state of the art routing protocols and it can be inferred that the proposed methodology comes up with improved results.

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“…Several reputation systems have been proposed for peer-to-peer networks [6,7], ad hoc networks [8][9][10], wireless sensor networks [11,12] and Internet of Vehicle [13][14][15]. However, these systems cannot be applied to VANETs in their existing forms they do not consider the main VANET characteristics: dynamicity and high speed.…”

Section: Related Workmentioning

confidence: 99%

“…Some of them [16,17] were proposed to deal with a specific type of message while others [3,6,19] used decentralized trust systems, relying on interactions with neighbors, which is not practical in the highly dynamic environment of a VANET. Several works [4,10,15,23] tried to cope with a specific type of attack, which can be a limitation whereas several others were designed to handle a specific challenge such as authentication [24], privacy [20,25] or localization [18,22]. Therefore, unlike other solutions, we propose an adaptive trust-based security scheme for message exchange in VANETs based on VGA, our new clustering algorithm designed to handle the dynamicity such networks.…”

Section: Related Workmentioning

confidence: 99%

TSME: a trust-based security scheme for message exchange in vehicular Ad hoc networks

Abassi

Douss

Sauveron

2020

Hum. Cent. Comput. Inf. Sci.

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A Vehicular Ad hoc NETwork (VANET) is a self-organized network formed by connected vehicles, which allows the exchange of useful traffic information in a timely manner. In such a context, evaluating the reliability of transmissions is vital. Trust can be used to promote such healthy collaboration. In fact, trust enables collaborating vehicles to counter uncertainty and suspicion by establishing trustworthy relationships. The main contribution of this paper is the proposition of a trust-based security scheme for message exchange in a VANET called TSME. Because of VANET characteristics, including dynamicity and high speed, we first proposed a VANET Grouping Algorithm (VGA); a suitable clustering algorithm organizing the network into groups with elected Group-Heads. Second, built on the VGA, we defined our trust management scheme dealing with vehicles’ reputations. Finally, we proposed a formal specification of the scheme using an inference system, and conducted a formal validation to assess its completeness and soundness rather than conducting simulations where some potentially rare conflicting or malfunctioning situations might not be detected. Soundness was proven by showing that there were no conflicts in our scheme, and completeness was established by assessing that all potential situations could be handled. The results obtained showed that our scheme for evaluating the veracity of exchanged messages is formally sound and complete.

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Analysis and Countermeasures of Black-Hole Attack in MANET by Employing Trust-Based Routing

Cited by 15 publications

References 20 publications

Detection of Black Hole Attack Using Honeypot Agent-Based Scheme with Deep Learning Technique on MANET

Detection of Black Hole Attack Using Honeypot Agent-Based Scheme with Deep Learning Technique on MANET

Host based Detection and Prevention of Black Hole attacks by AODV-ICCSO Algorithm for security in MANETs

TSME: a trust-based security scheme for message exchange in vehicular Ad hoc networks

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