Toward Incentivizing Fog-Based Privacy-Preserving Mobile Crowdsensing in the Internet of Vehicles

Sun, Gang; Sun, Siyu; Yu, Hongfang; Guizani, Mohsen

doi:10.1109/jiot.2019.2951410

Cited by 35 publications

(11 citation statements)

References 32 publications

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“…More importantly, since most data perturbation techniques introduce noises to the dataset, the data utility is reduced. In contrast with data perturbation, other research studies have applied cryptographic techniques (e.g., homomorphic encryption and public-private key signatures [40,41,49,50]) to protect users' privacy. Among all the cryptographic techniques, zero-knowledge proofs has been widely applied in areas such as blockchain (e.g., [11,15,28]), secure multi-party computation (e.g., [9,21]), and electronic voting or auctions (e.g., [18,37,38]).…”

Section: Crowdsensingmentioning

confidence: 99%

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Integrating IoT-Sensing and Crowdsensing with Privacy: Privacy-Preserving Hybrid Sensing for Smart Cities

Zhu,

Chau,

Guarddin

et al. 2022

Preprint

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Data sensing and gathering is an essential task for various information-driven services in smart cities. On the one hand, Internet of Things (IoT) sensors can be deployed at certain fixed locations to capture data reliably but suffer from limited sensing coverage. On the other hand, data can also be gathered dynamically through crowdsensing contributed by voluntary users but suffer from its unreliability and the lack of incentives for users' contributions. In this paper, we explore an integrated paradigm called "hybrid sensing" that harnesses both IoT-sensing and crowdsensing in a complementary manner. In hybrid sensing, users are incentivized to provide sensing data not covered by IoT sensors and provide crowdsourced feedback to assist in calibrating IoT-sensing. Their contributions will be rewarded with credits that can be redeemed to retrieve synthesized information from the hybrid system. In this paper, we develop a hybrid sensing system that supports explicit user privacy -IoT sensors are obscured physically to prevent capturing private user data, and users interact with a crowdsensing server via a privacy-preserving protocol to preserve their anonymity. A key application of our system is smart parking, by which users can inquire and find the available parking spaces in outdoor parking lots. We implemented our hybrid sensing system for smart parking and conducted extensive empirical evaluations. Finally, our hybrid sensing system can be potentially applied to other information-driven services in smart cities.

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Section: Crowdsensingmentioning

confidence: 99%

“…Particularly, the comparisons between our privacy-preserving hybrid sensing system with the aforementioned papers are tabulated in Table 1. 45,47,48] ✓ Data Perturbation ✓ × × [44] ✓ Data Perturbation × × × [40,41,49,50] ✓…”

Section: Comparisons To Our Workmentioning

confidence: 99%

Integrating IoT-Sensing and Crowdsensing with Privacy: Privacy-Preserving Hybrid Sensing for Smart Cities

Zhu,

Chau,

Guarddin

et al. 2022

Preprint

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“…Reputation mechanism has been widely used in wireless networks [32] and IoT systems to evaluate user reliability and detect malicious users. Sun et al [27] put forward the two-layer fog architecture in MCS-VANET, integrated the zero-knowledge proof technology into it, and evaluated the vehicle reputation according to the offset value of sensing data and the historical reputation value of PVs. Nan et al [28] proposed a CSII model based on cross-spatial multiple interaction to evaluate user reputation from four aspects: the data collecting time, the cover rate, the correlation, and historical reputation value.…”

Section: Reputation Mechanismmentioning

confidence: 99%

“…Reputation mechanism [27][28][29][30][31] The reputation of user is evaluated from multiple aspects.…”

Section: Research Categories Advantages Disadvantagesmentioning

confidence: 99%

An Efficient and Secure Malicious User Detection Scheme Based on Reputation Mechanism for Mobile Crowdsensing VANET

Wang

Guo

et al. 2021

Wireless Communications and Mobile Computing

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With the increasing development of wireless communication technology and Vehicular Ad hoc Network (VANET), as well as the continuous popularization of various sensors, Mobile Crowdsensing (MCS) paradigm has been widely concerned in the field of transportation. As a currently popular data sensing way, it mainly relies on wireless sensing devices to complete large-scale and complex sensing tasks. However, since vehicles are highly mobile in this scenario and the sensing system is open, that is, any vehicle equipped with sensing device can join the system, the credibility of all participating vehicles cannot be guaranteed. In addition, malicious users will upload false data in the sensing system, which makes the sensing data not meet the needs of the sensing tasks and will threaten traffic safety in some serious cases. There are many solutions to the above problems, such as cryptography, incentive mechanism, and reputation mechanisms. Unfortunately, although these schemes guaranteed the credibility of users, they did not give much thought to the reliability of data. In addition, some schemes brought a lot of overhead, some used a centralized server management architecture, and some were not suitable for the scenario of VANET. Therefore, this paper firstly proposes the MCS-VANET architecture-based blockchain, which consists of participating vehicles (PVs), road side units (RSUs), cloud server (CS), and the blockchain (BC), and then designs a malicious user detection scheme composed of three phases. In the data collecting phase, to reduce the data uploading overhead, data aggregation and machine learning technologies are combined by fully considering the historical reputation value of PVs, and the proportion of data uploading is determined based on the historical data quality evaluation result of PVs. In the data quality evaluation phase, a new reputation computational model is proposed to effectively evaluate the sensing data, which contains four indicators: the reputation history of PVs, the data unbiasedness, the leadership of PVs, and the spatial force of PVs. In the reputation updating phase, to achieve the effective change of reputation values, the logistic model function curve is introduced and the result of the reputation updating is stored in the blockchain for security publicity. Finally, on real datasets, the feasibility and effectiveness of our proposed scheme are demonstrated through the experimental simulation and security analysis. Compared with existing schemes, the proposed scheme not only reduces the cost of data uploading but also has better performance.

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“…Fog computing, as a new potential solution to improve the latency issue in cloud computing-based architectures [10], can be integrated into VANETs to decrease the transmission delay, provide reliable location awareness, and support access for more vehicles [11]. However, existing fog-based schemes do not provide for the protection of the privacy of vehicles.…”

Section: Introductionmentioning

confidence: 99%

Secure and Lightweight Conditional Privacy-Preserving Authentication for Fog-Based Vehicular Ad Hoc Networks

Zhong¹,

Chen²,

Zhang³

et al. 2022

IEEE Internet Things J.

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Vehicular Ad-Hoc Networks (VANETs) play an everincreasing important role in improving traffic management and enhancing driving safety. However, vehicular communication using a wireless channel faces security and privacy challenges. The Conditional Privacy-Preserving Authentication (CPPA) scheme is suitable for solving the above challenges, but the existing identity-based CPPA schemes suffer from inborn key escrow issues. Motivated by this, we propose a lightweight CPPA scheme based on elliptic curve cryptography to solve the above issues, in which the pseudonym and public/private key pair of the vehicle is generated by itself, so that the proposed scheme avoids the key escrow issue. Furthermore, to achieve efficient vehicular communication, a CPPA scheme is proposed using a fog computing model that supports mobility, low latency, and location awareness. The pseudonym of the vehicle is generated by two hash chains in the proposed scheme, so that the storage overhead can be reduced efficiently under the condition that backward security is guaranteed. Security analysis shows that the scheme is secure under the random oracle and satisfies the security requirements of VANETs. Performance evaluation demonstrates that the proposed scheme outperforms related schemes in terms of computational and communication overhead.

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Toward Incentivizing Fog-Based Privacy-Preserving Mobile Crowdsensing in the Internet of Vehicles

Cited by 35 publications

References 32 publications

Integrating IoT-Sensing and Crowdsensing with Privacy: Privacy-Preserving Hybrid Sensing for Smart Cities

Integrating IoT-Sensing and Crowdsensing with Privacy: Privacy-Preserving Hybrid Sensing for Smart Cities

An Efficient and Secure Malicious User Detection Scheme Based on Reputation Mechanism for Mobile Crowdsensing VANET

Secure and Lightweight Conditional Privacy-Preserving Authentication for Fog-Based Vehicular Ad Hoc Networks

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