Game-Theoretic Design of Optimal Two-Sided Rating Protocols for Service Exchange Dilemma in Crowdsourcing

Lu, Jianfeng; Xin, Yun; Zhang, Zhao; Liu, Xinwang; Li, Kenli

doi:10.1109/tifs.2018.2834318

Cited by 31 publications

(16 citation statements)

References 27 publications

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“…We hope to enrich the attack-defense methods against the CBTC system. We also intend to further study game theory [34,35] to reflect the attack-defense behavior more clearly and combine game theory with cybernetics [36,37] to improve system security.…”

Section: Discussionmentioning

confidence: 99%

Security Analysis for CBTC Systems under Attack–Defense Confrontation

2019

Electronics

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Communication-based train controls (CBTC) systems play a major role in urban rail transportation. As CBTC systems are no longer isolated from the outside world but use other networks to increase efficiency and improve productivity, they are exposed to huge cyber threats. This paper proposes a generalized stochastic Petri net (GSPN) model to capture dynamic interaction between the attacker and the defender to evaluate the security of CBTC systems. Depending on the characteristics of the system and attack–defense methods, we divided our model into two phases: penetration and disruption. In each phase, we provided effective means of attack and corresponding defensive measures, and the system state was determined correspondingly. Additionally, a semiphysical simulation platform and game model were proposed to assist the GSPN model parameterization. With the steady-state probability of the system output from the model, we propose several indicators for assessing system security. Finally, we compared the security of the system with single defensive measures and multiple defensive measures. Our evaluations indicated the significance of the defensive measures and the seriousness of the system security situation.

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Section: Discussionmentioning

confidence: 99%

Security Analysis for CBTC Systems under Attack–Defense Confrontation

2019

Electronics

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“…The former increases the task completer's inner satisfaction by improving its reputation, credit, or social status to ease the conflict between players. Some researchers create the rating protocol [14] to encourage players to adopt cooperative strategies. Lu et al [15] created a new social optimal rating protocol for price and reputation plan, which encourage layers to contribute more to gain even higher rewards.…”

Section: Mechanisms For Solving the Cooperation Dilemmamentioning

confidence: 99%

Two-Stage Game Design of Payoff Decision-Making Scheme for Crowdsourcing Dilemmas

Xia

Zhang

Cheng

et al. 2020

IEEE/ACM Trans. Networking

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Crowdsourcing uses collective intelligence to finish complicated tasks and is widely applied in many fields. However, the crowdsourcing dilemmas between the task requester and the task completer restrict the efficiency of system severely, e.g., the cooperation dilemma leads to the failure in the interactions and the quality of service dilemma results in the inability of task completer to provide high-quality service. Current research usually focuses on solving only one aforementioned dilemma and fails to integrate perfectly with the service architectural pattern of crowdsourcing systems. In this article, combined with the crowdsourcing interaction phase, we limit the objects that cause dilemma and propose a two-stage game payoff decision-making scheme (TGPD) to overcome these shortcomings. To solve the cooperation dilemma between the requester and the crowdsourcing platform, we first propose a dynamic payment method based on the reputation-quality rules for the task requester, and then develop a cos-evaluation algorithm to estimate platform's cost, last design a co-determine algorithm to determine whether the platform adopts a cooperative strategy. To address the quality of service dilemma between the crowdsourcing platform and the workers, we first present an auction-screening method to estimate the reasonable recruitment range of workers which can be optimized by the result of cos-evaluation algorithm, and then use a reward distribution method to motivate workers to complete tasks with high quality and on time. The experimental results indicate that our new scheme successfully increases the worker's and platforms' payoffs at the same time, improves the accuracy of screening workers, enhances the worker's quality of service, and decreases the platform's cost.

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“…Although the single iteration static model has research significance, the multiiteration dynamic model [26] is more suitable for the operation of mobile crowdsourcing market. Lu et al [27] formulated the service exchange between mobile contributors and crowdsourcing platform as an asymmetric game model. They proposed two-sided rating protocols for maximizing social welfare based on game-theoretic stimulated cooperation among contributors.…”

Section: Related Workmentioning

confidence: 99%

“…Solve (27) and we have the best response d * m i as (28). Since inviter r i senses tasks with WoM, we know that inviter r i is the second-hand contributor.…”

Section: ) F-st Stackelberg Gamementioning

confidence: 99%

How Mobile Contributors Will Interact With Each Other in Mobile Crowdsourcing With Word of Mouth Mode

Zeng

Wang

2019

IEEE Access

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Mobile crowdsourcing is a promising paradigm for collecting sensing data by leveraging contributions of numerous mobile smart phones. It works efficiently with Word of Mouth Mode (WoM), especially for sensing tasks with time and location constraints, since the sensing task can be spread quickly among mobile contributors in the WoM mode. In this paper, we first investigate the behaviors of contributors, categorize all contributors into four types according to their different behaviors, and propose an inviting algorithm for contributors to recruit cooperators through social closeness. Then, we design a reward mechanism for crowdsourcing platform to evaluate the budget and pay the reward to contributors, meanwhile stimulate contributors to make the maximum contribution. Furthermore, considering two different scenarios, we model the interactions among contributors as two Stackelberg games, and backward induction approach is used to analyze each game. We propose an algorithm to compute the best response of every contributor, and we theoretically prove that this proposed algorithm may converge a unique Stackelberg equilibrium. The proposed approach can be applied to task formulation and task budget evaluations for crowdsourcing platforms. INDEX TERMS Mobile crowdsourcing, word of mouth, game theory, Stackelberg game.

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Game-Theoretic Design of Optimal Two-Sided Rating Protocols for Service Exchange Dilemma in Crowdsourcing

Cited by 31 publications

References 27 publications

Security Analysis for CBTC Systems under Attack–Defense Confrontation

Security Analysis for CBTC Systems under Attack–Defense Confrontation

Two-Stage Game Design of Payoff Decision-Making Scheme for Crowdsourcing Dilemmas

How Mobile Contributors Will Interact With Each Other in Mobile Crowdsourcing With Word of Mouth Mode

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