Game Theoretical Defense Mechanism Against Reputation Based Sybil Attacks

Kumar, Bhupender; Bhuyan, Bubu

doi:10.1016/j.procs.2020.03.299

Cited by 12 publications

(29 citation statements)

References 15 publications

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“…DTMS focuses on real-time detection of Sybil attacks and on-off attacks in WSNs through an efficient multi-level detection algorithm. It solves the limitations/shortcomings of the previous work [2][3][4][5] Moreover, it provides the comparative result analysis in terms of severity analysis, true detection rate and false detection rate, residual energy, packet loss rate, network lifetime, etc. The last section 5 presents the conclusion and future directions for developing an efficient trust model.…”

Section: Our Scientific Contributionmentioning

confidence: 99%

“…NoSad constitutes various scenarios to counter the Sybil attack; however, it is ineffective if the number of Sybil nodes is less than three. In [5], the author proposes a static game theory approach to defend against Sybil's attack. It depends on zero-sum and imperfect information.…”

Section: Related Workmentioning

confidence: 99%

“…The first and second attack models were simulated and repeated 50 times to validate the DTMS protocol, and the results were averaged to arrive at the final value. We compare DTMS with [2][3][4] [5] in terms of True detection rate (TDR), False detection rate (FDR) network lifetime, energy consumption and packet loss ratio." Figure 4 shows the performance metrics used in DTMS.…”

Section: ) Ifmentioning

confidence: 99%

“…It shows a consistent increase in the trust values with the change in success rate(%). In GameTrust [5] model, trust values are highly fluctuating when the success rate is increasing.…”

Section: I) Severity Analysismentioning

confidence: 99%

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DTMS: A Dual Trust-based Multi-level Sybil Attack Detection Approach in WSNs

Khan

Singh

2023

Preprint

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Sensor network has been proven a promising technology for discerning data as well as details about the physical world. The sensor nodes are organized and positioned in an inaccessible and hostile environment and are consequently susceptible to various security attacks. Among the multiple attacks possible in any WSN, the Sybil attack is the most severe kind of attack. Detection of a Sybil node is a complex as well as challenging problem since it illegitimately uses multiple fraudulent identities to misguide and collapse the network. The paper proposes a dual trust-based multi-level Sybil (DTMS) attack detection approach in WSNs. The work engages a multi-level detection system grounded on verification of the node’s identity and location. Later, at each level, CM, CH, and BS, the trust value is calculated. For a satisfactory level of trust value, communication trust is calculated together with data trust. The trust function of DTMS involves dynamic reward and penalty coefficient to ensure severity. Besides, data aggregation is employed, which contributes to lesser communication overhead and energy consumption. The performance evaluation of DTMS is measured in terms of severity of trust function, true detection rate, false detection rate, residual energy, network lifetime, and packet loss ratio. The simulation results validate that DTMS can efficaciously detect Sybil nodes. Experiment results show that the proposed algorithm can detect [[EQUATION]] of Sybil nodes in the malicious environment. Additionally, the DTMS is compared with recent existing schemes in terms of various parameters (True Detection Rate, False Detection Rate, energy consumption, packet loss rate, number of alive nodes, etc.) which show that the DTMS performs desirably.

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Section: Our Scientific Contributionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: ) Ifmentioning

confidence: 99%

“…It shows a consistent increase in the trust values with the change in success rate(%). In GameTrust [5] model, trust values are highly fluctuating when the success rate is increasing.…”

Section: I) Severity Analysismentioning

confidence: 99%

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DTMS: A Dual Trust-based Multi-level Sybil Attack Detection Approach in WSNs

Khan

Singh

2023

Preprint

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“…Although filters for checking the authenticity of reviews are necessary, studies show that still many reviews and ratings are fake, and filters cannot prevent them [3,4]. On the other hand, despite the fact that sybil attacks have been widely studied in various networks [9,10,18], such studies especially targeted towards preventing sybil attacks on rating systems are few and far between.…”

Section: Related Workmentioning

confidence: 99%

RewardRating: A Mechanism Design Approach to Improve Rating Systems

Vakilinia,

Faizian,

Khalili

2021

Preprint

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Nowadays, rating systems play a crucial role in the attraction of customers for different services. However, as it is difficult to detect a fake rating, attackers can potentially impact the rating's aggregated score unfairly. This malicious behavior can negatively affect users and businesses. To overcome this problem, we take a mechanism-design approach to increase the cost of fake ratings while providing incentives for honest ratings. Our proposed mechanism RewardRating is inspired by the stock market model in which users can invest in their ratings for services and receive a reward based on future ratings. First, we formally model the problem and discuss budget-balanced and incentive-compatibility specifications. Then, we suggest a profit-sharing scheme to cover the rating system's requirements. Finally, we analyze the performance of our proposed mechanism.

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A Game-Based Approach for Mitigating the Sybil Attacks on Blockchain Applications

Samanta,

Chaki

2023

Lecture Notes in Computer Science

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Game Theoretical Defense Mechanism Against Reputation Based Sybil Attacks

Cited by 12 publications

References 15 publications

DTMS: A Dual Trust-based Multi-level Sybil Attack Detection Approach in WSNs

DTMS: A Dual Trust-based Multi-level Sybil Attack Detection Approach in WSNs

RewardRating: A Mechanism Design Approach to Improve Rating Systems

A Game-Based Approach for Mitigating the Sybil Attacks on Blockchain Applications

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