Selfish Node Detection by Modularized Deep NMF Autoencoder Based Incentivized Reputation Scheme

Sharma, Rakhi; Dinkar, Shail Kumar

doi:10.1080/01969722.2022.2080337

Cited by 6 publications

(2 citation statements)

References 27 publications

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“…Sharma and Dinkar [24] have designed a reputation strategy using incentives which was determined by clustering the social features of cooperating mobile nodes depending on the computation of weighted social tie. This reputation mechanism depends on the strength of social connections and updates the social tie weight depending on the incentives provided as penalty and reward in the network.…”

Section: Yamini Et Al (2022) Have Proposed An Effective Trustmentioning

confidence: 99%

Selfish Node Detection Scheme based on Bates Distribution Inspired Trust Factor for MANETs

Janakiraman¹,

Priya²

2023

EAI Endorsed Trans Energy Web

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The trustworthiness of mobile nodes is considered as the principal parameter for ensuring significant data dissemination in a Mobile Ad hoc NETwork (MANET). However, the selfish behaviour of nodes minimizes the trust by dropping a considerable amount of data packets in the network. The significant dropping of data packets by the selfish node introduces huge data overhead with increased latency and energy consumption, thus increasing the number of retransmissions. In this paper, Selfish Node Detection Scheme based on Bates Distribution Inspired Trust Factor (SNDS-BDITF) is propounded for predominant detection of selfish behaviour by investigating multiple levels of factors that contribute towards effective selfishness detection. The proposed SNDS-BDITF approach is also potent in enhancing the detection rate of selfishness by multi-perspective analysis of each monitored node’s forwarding characteristics considering the benefits of other cooperating mobile nodes. The simulation results of the propounded SNDS-BDITF method are enhanced on an average by 16% and 14% when compared to the existing selfish node segregation mechanisms prevalent in the literature.

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Section: Yamini Et Al (2022) Have Proposed An Effective Trustmentioning

confidence: 99%

Selfish Node Detection Scheme based on Bates Distribution Inspired Trust Factor for MANETs

Janakiraman¹,

Priya²

2023

EAI Endorsed Trans Energy Web

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“…Malicious/Selfish nodes are one of the key challenging security issue in DTNs [16], [17]. Malicious/Selfish nodes introduce variously attacks such as Packet-Flooding [8], [9], [18], [19], Packet-Drooping (there are various categories of Packet-Dropping attacks.…”

Section: Introductionmentioning

confidence: 99%

FAPMIC: Fake Packet and Selective Packet Drops Attacks Mitigation by Merkle Hash Tree in Intermittently Connected Networks

et al. 2023

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Delay/Disruption Tolerant Networks (DTNs) are a special category of IntermittentlyCon-nectedNetworks (ICNs). It has features such as long-delay, frequent-disruption, asymmetrical-data-rates, and high-bundle-error-rates. DTNs have been mainly developed for planet-to-planet networks, commonly known as Inter-Planetary-Networks (IPNs). However, DTNs have shown undimmed potency in challenged communication networks, such as DakNet, ZebraNet, KioskNet and WiderNet. Due to unique characteristics (Intermittent-connectivity and long-delay) DTNs face tough/huge/several challenges in various research areas i.e bundle-forwarding, key-distribution, privacy, bundle-fragmentation, and malicious/selfish nodes particularly. Malicious/selfish nodes launch various catastrophic attacks, this includes, fake packet attacks, selective packet drops attacks, and denial-of-service/flood attacks. These attacks inevitably consume limited resources (persistent-buffer and bandwidth) in DTNs. Fake-packet and selective-packet-drops attacks are top among the challenging attacks in ICNs. The focus of this article is on critical analyses of fake-packet and selective-packet-drops attacks. The panoramic view on misbehavior nodes mitigation algorithms are analyzed, and evaluated mathematically through several parameters for detection probability/accuracy. This article presents a novel algorithm to detects/mitigates fake-packet and selective-packet-drops attacks. Trace-driven simulation results show the proposed algorithm of this article accurately (enhanced detectionaccuracy, reduces false-positive/false-negative rates) detects malicious nodes which launch fake-packet and selective-packet-drops attacks, unlike previously proposed algorithms which detect only one attack (fakepacket or packet-drops at a time) or detect only malicious path (do not exactly detect malicious nodes which launch attacks).

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Modified clustering and incentivized stable CH selection for reliable VANET communication

Kumari,

Kumar,

Raw

2024

Cluster Comput

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Selfish Node Detection by Modularized Deep NMF Autoencoder Based Incentivized Reputation Scheme

Cited by 6 publications

References 27 publications

Selfish Node Detection Scheme based on Bates Distribution Inspired Trust Factor for MANETs

Selfish Node Detection Scheme based on Bates Distribution Inspired Trust Factor for MANETs

FAPMIC: Fake Packet and Selective Packet Drops Attacks Mitigation by Merkle Hash Tree in Intermittently Connected Networks

Modified clustering and incentivized stable CH selection for reliable VANET communication

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