Poster: Smart-Contract Based Incentive Mechanism for K-Anonymity Privacy Protection in LBSs

Geng, Ziye; He, Yunhua; Niu, Tong; Li, Hong; Sun, Limin; Cheng, Wei Cherng; Xu, Li

doi:10.1109/pac.2017.33

Cited by 6 publications

(4 citation statements)

References 2 publications

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“…To avoid the usage of TTS secure systems, BC SC technology is beneficial. Geng et al [34] introduced an enhanced k-anonymity approach to use for privacy protection with SC. It is a BC-based secure incentive mechanism that motivates users to prefer a k-anonymity algorithm for privacy preservation.…”

Section: A Privacy-preserving Artificial Intelligence Techniquesmentioning

confidence: 99%

“…Data stored in SCs can be visible to anyone as it is in plain text; an attacker can read the contract and track the information of the requester. This issue is addressed by Geng et al [34], they have used public and private contract approach where private contracts can only be accessed by users who are participants of the k-anonymous group. Group encryption is used to keep the public contract secret, and to verify the contract, blind collective DS (digital signature) is used.…”

Section: A Privacy-preserving Artificial Intelligence Techniquesmentioning

confidence: 99%

“…Mamoshina et al [33] focused on using AI and BC for bio-medical research. Geng et al [34] proposed a secure authentication model for BC with k-anonymity. Dinh and Thai [35] focused on integration of AI and BC.…”

Section: Introductionmentioning

confidence: 99%

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Smart Contract Privacy Protection Using AI in Cyber-Physical Systems: Tools, Techniques and Challenges

et al. 2020

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Applications of Blockchain (BC) technology and Cyber-Physical Systems (CPS) are increasing exponentially. However, framing resilient and correct smart contracts (SCs) for these smart application is a quite challenging task because of the complexity associated with them. SC is modernizing the traditional industrial, technical, and business processes. It is self-executable, self-verifiable, and embedded into the BC that eliminates the need for trusted third-party systems, which ultimately saves administration as well as service costs. It also improves system efficiency and reduces the associated security risks. However, SCs are well encouraging the new technological reforms in Industry 4.0, but still, various security and privacy challenges need to be addressed. In this paper, a survey on SC security vulnerabilities in the software code that can be easily hacked by a malicious user or may compromise the entire BC network is presented. As per the literature, the challenges related to SC security and privacy are not explored much by the authors around the world. From the existing proposals, it has been observed that designing a complex SCs cannot mitigate its privacy and security issues. So, this paper investigates various Artificial Intelligence (AI) techniques and tools for SC privacy protection. Then, open issues and challenges for AI-based SC are analyzed. Finally, a case study of retail marketing is presented, which uses AI and SC to preserve its security and privacy.

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Section: A Privacy-preserving Artificial Intelligence Techniquesmentioning

confidence: 99%

Section: A Privacy-preserving Artificial Intelligence Techniquesmentioning

confidence: 99%

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Smart Contract Privacy Protection Using AI in Cyber-Physical Systems: Tools, Techniques and Challenges

et al. 2020

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“…A contractual agreement between all the participants is set up not to leak this information to the external parties. Anonymity is an effective way to protect participants' personal data [27] and the DSO system will also protect the data against cyber-attacks.…”

Section: Blockchain For P2p Energy Exchangementioning

confidence: 99%

Blockchain for peer-to-peer energy trading

Yang¹

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First and foremost, I would like to express my greatest gratitude to my supervisor Assoc. Prof. Gooi Hoay Beng, whose guidance and endless patience helped me to complete my master studies. His willingness to share his resources had provided me with the biggest support in my research work. I am also heartily thankful to him and Mrs Gooi who took great care of me when I was in the hospital. Their generous and positive view of life will affect me for good. I would like to express my sincere thanks to my colleague and also my good friend, Mr. Paudel, who offered me tremendous support in experimental methods and research skills. I feel so grateful for his encouragement and inspiration, which helped me to overcome the difficulties I have ever encountered in my research.

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IFTS: A Location Privacy Protection Method Based on Initial and Final Trajectory Segments

Liu

Zhang

et al. 2021

IEEE Access

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Privacy protection problem is one of the most concerning issues related to Location-Based Services (LBS) in our daily life. Privacy protection of LBS often requires anonymizing customer's trajectory data. Currently available methods for trajectory anonymity often assume an entire trajectory as one anonymous unit, which may lead to low anonymity efficiency due to the massive amount of trajectory data, especially for customers travel through a long road. Considering people's routine activities, the starting and ending locations of a trip often uncover the user's request intent, which may lead to exposure of user privacy. In order to address the problem of inefficient trajectory anonymity, we propose a location privacy protection method that is based on the initial and final trajectory segmentation (IFTS) in this paper. In the IFTS method, the road network structure is first transformed into an edge cluster model based on its location type. Then, the user trajectory is divided to segments according to the temporal sequence of the ingress and egress nodes. The initial and final trajectory segments are identified and divided into equivalence classes, which then are used for constructing a trajectory graph and the corresponding k-anonymous set. Our experimental results show that the proposed method can reduce the anonymous area, improve anonymity efficiency, and enhance trajectory data utilization compared to the existing methods for trajectory anonymity.INDEX TERMS Location based service (LBS), location privacy, k-anonymity, initial and final trajectory segments (IFTS).

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Poster: Smart-Contract Based Incentive Mechanism for K-Anonymity Privacy Protection in LBSs

Cited by 6 publications

References 2 publications

Smart Contract Privacy Protection Using AI in Cyber-Physical Systems: Tools, Techniques and Challenges

Smart Contract Privacy Protection Using AI in Cyber-Physical Systems: Tools, Techniques and Challenges

Blockchain for peer-to-peer energy trading

IFTS: A Location Privacy Protection Method Based on Initial and Final Trajectory Segments

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