A Blockchain-based privacy preserving mechanism for mobile crowdsensing
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Abstract
In blockchain-based mobile crowdsensing, reporting of real-time data is stored on a public blockchain in which the address of every user/node is public. Now, the problem lies in the fact that if their addresses get shown to adversaries, all their transactions history is also going to be revealed. Therefore, crowdsensing demands a little privacy preservation strategy in which the identity of a user is unable to be revealed to an adversary or we can say that crowd sensors while reporting the real-time data must provide some level of anonymity to crowdsensing users/nodes [1]. The current crowdsensing architecture is not secure because of its centralized nature and the reason is a single point of failure also numerous kinds of attacks are possible by adversaries such as linkage attacks, Sybil attacks, and DDOS attacks to get the identity or any other valuable information about the nodes. The location of crowd sensors is also a threat that could lead to adversarial attacks. Consequently, some blockchain-based models must be proposed to attain privacy on the blockchain ledger. The solution can either be made up crowdsensing environment on a private blockchain or smart contracts may be the answer to this problem by which we can make the users secure from several attacks conducted by adversaries on the blockchain.
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Ul Hassan M, Rehmani MH, Chen J (2019) Privacy Preservation in Blockchain- Based IoT Systems: Integration Issues, Prospects, Challenges, and Future Research Directions. Future Gen Compu Syst 97: 512-529. Link: https://bit.ly/3HIMEBV
Zhuo G, Jia Q, Guo L, Li M, Li P (2017) Privacy- Preserving Verifiable Set Operation in Big Data for Cloud- Assisted Mobile Crowdsourcing. IEEE Internet Things J 4: 572-582. Link: https://bit.ly/3uxTGpr
Kim JW, Edemacu K, Jang B (2022) Privacy-preserving mechanisms for location privacy in mobile crowdsensing: A survey. J Netw Comput Appl 200: 103315. Link: https://bit.ly/3LlgcIc
Miers I, Garman C, Green M, Rubin AD (2013) Zerocoin: Anonymous Distributed E-Cash from Bitcoin. 2013 IEEE Symposium on Security and Privacy, Berkeley, CA 397-411. Link: https://bit.ly/3gyMnFL
Li L, Liu J, Cheng L, Qiu S, Wang W, et al. (2018) CreditCoin: A Privacy-Preserving Blockchain-Based Incentive Announcement Network for Communications of Smart Vehicles. IEEE trans Intell Transp Syst 19: 2204-2220. Link: https://bit.ly/3uRCHPd
Zhu S, Li W, Cai Z, Hu H, Li Y (2020) zkCrowd: A Hybrid Blockchain-Based Crowdsourcing Platform. IEEE Trans Industr Inform 16: 4196-4205. Link: https://bit.ly/35O3rFx
Yang K, Zhang K, Ren J, Shen X (2015) Security and privacy in mobile crowdsourcing networks: challenges and opportunities. IEEE Commun Mag 53: 75-81. Link: https://bit.ly/35PTIP2
Buddhadeb H (2017) Crowdsourcing crisis management platforms: a privacy and data protection risk assessment and recommendations. Link: https://bit.ly/3LoyvMn
Li M, Weng J, Yang A, Lu W, Zhang Y, et al. (2019) CrowdBC: A Blockchain-Based Decentralized Framework for Crowdsourcing. IEEE Trans Parallel Distrib Syst 30: 1251-1266. Link: https://bit.ly/3HGqoZn
To H, Ghinita G, Fan L, Shahabi C (2017) Differentially Private Location Protection for Worker Datasets in Spatial Crowdsourcing. IEEE Trans Mob Comput 16: 934-949. Link: https://bit.ly/3LnBzZm
Ni T, Chen Z, Xu G, Zhang S, Zhong H (2021) Differentially private double auction with reliability-aware in mobile crowd sensing. Ad Hoc Networks 114: 102450. Link: https://bit.ly/3GDBsp1
Wang Z, Li J, Hu J, Ren J, Wang Q, et al. (2021) Towards privacy-driven truthful incentives for mobile crowdsensing under untrusted platform. IEEE Trans Mob Comput. Link: https://bit.ly/34l7okZ
Li Z, Liu J, Hao J, Wang H, Xian M (2020) CrowdSFL: A Secure Crowd Computing Framework Based on Blockchain and Federated Learning. MDPI. Link: https://bit.ly/3spUkCJ
García VJ, Calvo A, Hassan S, Sánchez-Ruiz AA (2016) Betfunding: A distributed bounty- based crowdfunding platform over ethereum. Distributed Computing and Artificial Intelligence, 13th International Conference 403-411. Link: https://bit.ly/3uCBrPF
Zhu H, Zhou ZZ (2016) Analysis and outlook of applications of blockchain technology to equity crowdfunding in China. Finance Innov 2: 29. Link: https://bit.ly/3gAnTfm
Buccafurri F, Lax G, Nicolazzo S, Nocera A (2017) Tweetchain: An Alternative to Blockchain for Crowd-Based Applications. ICWE. Link: https://bit.ly/3oClmpj
Wu HT, Tsai C (2018) Toward Blockchains for Health-Care Systems: Applying the Bilinear Pairing Technology to Ensure Privacy Protection and Accuracy in Data Sharing. IEEE Consum Electron Mag 7: 65-71. Link: https://bit.ly/364VtZ3
Zhang A, Lin X (2018) Towards Secure and Privacy-Preserving Data Sharing in e- Health Systems via Consortium Blockchain. J Med Syst 42: 140. Link: https://bit.ly/3gBW46p
Shetty S, Kamhoua CA, Njilla LL (2019) Blockchain for Distributed Systems Security. 352. Link: https://bit.ly/3uxTzdv
Li M, Zhu L, Lin X (2020) Efficient and Privacy-Preserving Carpooling Using Blockchain- Assisted Vehicular Fog Computing. IEEE Internet Things J 1. Link: https://bit.ly/3rBQO9d
Svetinovic D (2018) Security and Privacy in Decentralized Energy Trading Through Multi-Signatures, Blockchain and Anonymous Messaging Streams. IEEE Trans Dependable Secure Comput 15: 840- 852.
Nakamoto S (2020) Bitcoin: A Peer-to-Peer Electronic Cash System. Link: https://bitcoin.org/bitcoin.pdf
Alsheikh MA, Jiao Y, Niyato D, Wang P, Leong D, et al. (2017) The Accuracy- Privacy Tradeoff of Mobile Crowdsensing. IEEE Commun Mag 55. Link: https://bit.ly/34HbYJW