A Secure Incentive Mechanism for Competitive Organization Data Sharing: A Contract Theoretic Approach

Guo, Bo; Deng, Xinyang; Tian, Jie; Guan, Quansheng; Zheng, Xiangwei

doi:10.1109/access.2019.2915387

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…In the study on the motivations for data sharing, Guo et al (2018) established the idea of data competitiveness. Based on considering data competition, Guo et al (2019) adopted differential privacy to secure privacy and proposed a contract theory method to develop incentive mechanisms.…”

Section: Related Workmentioning

confidence: 99%

A dynamic incentive mechanism for data sharing in manufacturing industry

Liu,

Yu,

Huang

2024

10.5267/j.ijiec

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Data sharing is a critical component in a blockchain traceability platform. Therefore, creating a reasonable incentive mechanism to ensure that all enterprises participate in data sharing is vital for blockchain platforms. Currently, many researchers employ evolutionary game theory to analyze problems related to data sharing. However, evolutionary game theory typically assumes that the population composed of enterprises is mixed uniformly. Enterprises in the manufacturing industry are not uniformly mixed, as they tend to have specific connections with each other due to the size of enterprises and volume of business. Therefore, a networked evolutionary game is introduced to solve this problem. Firstly, an incentive model for enterprises sharing data is established. Then, a scale-free network is employed to simulate the connections between enterprises. To comprehensively consider the individual and group benefits of enterprises in the game, this study designs a strategy update rule for networked evolutionary game based on Discrete Particle Swarm Optimization and Variable Neighborhood Descent algorithm. To tackle the challenge of determining reasonable incentive values in networked evolutionary games, this study proposes a dynamic incentive mechanism based on the Q-Learning algorithm. Finally, the experiments indicate that this method can successfully facilitate the stable involvement of enterprises in data sharing.

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Section: Related Workmentioning

confidence: 99%

A dynamic incentive mechanism for data sharing in manufacturing industry

Liu,

Yu,

Huang

2024

10.5267/j.ijiec

View full text Add to dashboard Cite

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“…Therefore, we are in need of privacy-preserving techniques to strengthen the data sharing models. To motivate data sharing for data holders, the work in [57] proposed a competitiveness-driven and secure incentive mechanism. The proposed research is based on a data competitiveness model, where the data holders share data with demanders and earn data competitiveness from data demanders by eliminating the competitiveness worry, inducing win-win results for data holders and the demander.…”

Section: A Incentives For Iot Data Sharingmentioning

confidence: 99%

Incentive techniques for the Internet of Things: A survey

Maddikunta

Pham

Nguyen

et al. 2022

Journal of Network and Computer Applications

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“…Therefore, cyber-incident information sharing technology needs to identify the information type and how it is collected, stored, and processed [6]. However, the problem is that various organizations are reluctant to share their cyberincident information and trust those who have it [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

PURA-SCIS Protocol: A Novel Solution for Cloud-Based Information Sharing Protection for Sectoral Organizations

et al. 2021

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Over recent years, the incidence of data breaches and cyberattacks has increased significantly. This has highlighted the need for sectoral organizations to share information about such events so that lessons can be learned to mitigate the prevalence and severity of cyber incidents against other organizations. Sectoral organizations embody a governance relationship between cross-sector public and private entities, called public-private partnerships (PPPs). However, organizations are hesitant to share such information due to a lack of trust and business-critical confidentially issues. This problem occurs because of the absence of any protocols that guarantee privacy protection and protect sensitive information. To address this issue, this paper proposes a novel protocol, Putra-Ramli Secure Cyber-incident Information Sharing (PURA-SCIS), to secure cyber incident information sharing. PURA-SCIS has been designed to offer exceptional data and privacy protection and run on the cloud services of sectoral organizations. The relationship between organizations in PURA-SCIS is symmetrical, where the entities must collectively maintain the security of classified cyber incident information. Furthermore, the organizations must be legitimate entities in the PURA-SCIS protocol. The Scyther tool was used for protocol verification in PURA-SCIS. The experimental results showed that the proposed PURA-SCIS protocol provided good security properties, including public verifiability for all entities, blockless verification, data privacy preservation, identity privacy preservation and traceability, and private information sharing. PURA-SCIS also provided a high degree of confidentiality to protect the security and integrity of cyber-incident-related information exchanged among sectoral organizations via cloud services.

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A Secure Incentive Mechanism for Competitive Organization Data Sharing: A Contract Theoretic Approach

Cited by 5 publications

References 33 publications

A dynamic incentive mechanism for data sharing in manufacturing industry

A dynamic incentive mechanism for data sharing in manufacturing industry

Incentive techniques for the Internet of Things: A survey

PURA-SCIS Protocol: A Novel Solution for Cloud-Based Information Sharing Protection for Sectoral Organizations

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