Vehicular CrowdSensing (VCS) has become a promising paradigm to employ mobile vehicles for performing sensing tasks in supporting location-based services and applications. In traditional VCS, a central agency is highly depended on, from collecting task requests of requesters to employment and reward assignment to workers. However, the centralized manner causes critical problems, such as potential privacy leakage and unexpected free-riding and false-reporting behaviors due to the lack of recorded proofs. The challenging problems hinder the wide-spread deployment of VCS. In this paper, we utilize consomum blockchain to elaborately design a dedicated blockchain, called by VeSenChain, to provision VCS services in a decentralized, authentic and transparent manner. For the implementation of VeSenChain, we develop an interactive protocol to support smart contract based operations among different entities. Stackelberg game approach is further used to formulate and solve the sensing task scheduling problem between a requester and multiple workers, and thus enable optimal smart contract design. Numerical results demonstrate that VeSenChain is effective and efficient for promoting VCS in network security and efficiency.
The ever increasing amount of personal data accumulated by companies offering innovative services through the cloud, Internet of Things devices and, more recently, social robots has started to alert consumers and legislative authorities. In the advent of the first modern laws trying to protect user privacy, such as the European Union General Data Protection Regulation, it is still unclear what are the tools and techniques that the industry should employ to comply with regulations in a transparent and cost effective manner. We propose an architecture for a public blockchain based ledger that can provide strong evidence of policy compliance. To address scalability concerns, we define a new type of off-chain channel that is based on general state channels and offers verification for information external to the blockchain. We also create a model of the business relationships in a smart home setup that includes a social robot and suggest a sticky policy mechanism to monitor cross-boundary policy compliance.
Christian Rondanini, Barbara Carminati, Elena Ferrari
Selection criteria regulating IoT device discovery involve confidentiality issue on the information the constraints convey. A promising approach to cope with this issue is leveraging on blockchain technology and smart contracts to implement the overall discovery process deployment. However, due to the blockchain design, data within the blockchain is public and smart contracts cannot access data outside the blockchain, unless through the exploitation of Oracles. On the one hand, this brings benefits of trust decentralization, transparency, and accountability of the discovery process. On the other hand, it carries serious consequences on confidentiality and privacy as well as on Oracles trustworthiness. For these reasons, in this paper, we investigate how to ensure data confidentiality during the discovery process of IoT devices on blockchain even in the presence of an untrusted Oracle.
IoT devices produce a lot of valuable and sensitive data that is often shared with external parties to provide different kinds of useful services. Traditional IoT access control systems are centralized and do not include all the stakeholders in the access control decision making process. To fill this gap, we propose a permissioned blockchain based access control system for IoT where a different phase of access control like creating access policy and making the access control decision happens based on the consensus of all the stakeholders. To be more specific, we design and implement Attribute Based Access Control (ABAC) in a permissioned blockchain called Hyperledger Fabric and leverage its smartcontract and distributed consensus to enable a distributed access control for IoT. The effectiveness of our proposed system is demonstrated by the performance evaluation result in an IoT testbed.
This paper looks at the development of blockchain technologies that promise to bring new tools for the management of private data, providing enhanced security and privacy to individuals. Particular interest presents solutions aimed at reorganizing data flows in the Internet of Things (IoT) architectures, enabling the secure and decentralized exchange of data between network participants. However, as this paper argues, the promised benefits are counterbalanced by a significant shift towards the propertization of private data, underlying these proposals. Considering the unique capacity of blockchain technology applications to imitate and even replace traditional institutions, this aspect may present certain challenges, both of technical and ethical character. In order to highlight these challenges and associated concerns, this paper identifies the underlying techno-economic factors and normative assumptions defining the development of these solutions amounting to technologically enabled propertization. It is argued that without careful consideration of a wider impact, such blockchain applications could have effects opposite to the intended ones, thus contributing to the erosion of privacy for IoT users.
Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan · 5 authors
Internet-of-Things (IoT) companies strive to get feedback from users to improve their products and services. However, traditional surveys cannot reflect the actual conditions of customers' due to the limited questions. Besides, survey results are affected by various subjective factors. In contrast, the recorded usages of IoT devices reflect customers' behaviours more comprehensively and accurately. We design an intelligent system to help IoT device manufacturers to take advantage of customers' data and build a machine learning model to predict customers' requirements and possible consumption behaviours with federated learning (FL) technology. The FL consists of two stages: in the first stage, customers train the initial model using the phone and the edge computing server collaboratively. The mobile edge computing server's high computation power can assist customers' training locally. Customers first collect data from various IoT devices using phones, and then download and train the initial model with their data. During the training, customers first extract features using their mobiles, and then add the Laplacian noise to the extracted features based on differential privacy, a formal and popular notion to quantify privacy. After achieving the local model, customers sign on their models respectively and send them to the blockchain. We use the blockchain to replace the centralized aggregator which belongs to the third party in FL. In the second stage, miners calculate the averaged model using the collected models sent from customers. By the end of the crowdsourcing job, one of the miners, who is selected as the temporary leader, uploads the model to the blockchain. Besides, to attract more customers to participate in the crowdsourcing FL, we design an incentive mechanism, which awards participants with coins that can be used to purchase other services provided by the company.
Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan · 8 authors
Home appliance manufacturers strive to obtain feedback from users to improve their products and services to build a smart home system. To help manufacturers develop a smart home system, we design a federated learning (FL) system leveraging the reputation mechanism to assist home appliance manufacturers to train a machine learning model based on customers' data. Then, manufacturers can predict customers' requirements and consumption behaviors in the future. The working flow of the system includes two stages: in the first stage, customers train the initial model provided by the manufacturer using both the mobile phone and the mobile edge computing (MEC) server. Customers collect data from various home appliances using phones, and then they download and train the initial model with their local data. After deriving local models, customers sign on their models and send them to the blockchain. In case customers or manufacturers are malicious, we use the blockchain to replace the centralized aggregator in the traditional FL system. Since records on the blockchain are untampered, malicious customers or manufacturers' activities are traceable. In the second stage, manufacturers select customers or organizations as miners for calculating the averaged model using received models from customers. By the end of the crowdsourcing task, one of the miners, who is selected as the temporary leader, uploads the model to the blockchain. To protect customers' privacy and improve the test accuracy, we enforce differential privacy on the extracted features and propose a new normalization technique. We experimentally demonstrate that our normalization technique outperforms batch normalization when features are under differential privacy protection. In addition, to attract more customers to participate in the crowdsourcing FL task, we design an incentive mechanism to award participants.
Security of IoT devices and applications can be improved by using the emerging Blockchain Technology which uses decentralised interaction and scalable architectures with security and distributed trust. In this work a review of Lightweight scalable Blockchain is proposed for security and privacy of IoT devices. An IoT scenario of smart home is used for illustrative purposes but this proposed architecture is wellsuited for diverse IoT applications. Effectiveness of this architecture is analysed using common threat models which provides an appropriate assessment for security and privacy implementation for smart home.
It has been a decade since the concept of blockchain was invented as the underlying core data structure of the permissionless or public Bitcoin cryptocurrency network. Since then, several cryptocurrencies, tokens and ICOs have emerged. After much speculation and hype, significant number of them have become problematic or worthless! The public blockchain system Ethereum emerged by generalizing the use of blockchains to manage any kind of asset, be it physical or purely digital, with the introduction of Smart Contracts. Over the years, numerous myths have developed with respect to the purported utility and the need for public blockchains. The adoption and further adaptation of blockchains and smart contracts for use in the permissioned or private environments is what I consider to be useful and of practical consequence. Hence, the technical aspects of only private blockchain systems will be the focus of my SIGMOD 2019 keynote. Along the way, I will bust many myths associated with public blockchains. I will also compare traditional database technologies with blockchain systems' features and identify desirable future research topics.
Blockchain has the potential to render the transaction of information more secure and transparent. Nowadays, transportation data are shared across multiple entities using heterogeneous mediums, from paper collected data to smartphone. Most of this data are stored in central servers that are susceptible to hacks. In some cases shady actors who may have access to such sources, share the mobility data with unwanted third parties. A multi-layered Blockchain framework for Smart Mobility Data-market (BSMD) is presented for addressing the associated privacy, security, management, and scalability challenges. Each participant shares their encrypted data to the blockchain network and can transact information with other participants as long as both parties agree to the transaction rules issued by the owner of the data. Data ownership, transparency, auditability and access control are the core principles of the proposed blockchain for smart mobility data-market. In a case study of real-time mobility data sharing, we demonstrate the performance of BSMD on a 370 nodes blockchain running on heterogeneous and geographically-separated devices communicating on a physical network. We also demonstrate how BSMD ensures the cybersecurity and privacy of individual by safeguarding against spoofing and message interception attacks and providing information access management control.
Blockchain technology is heralded for improving trust and can provide a new approach for creating transparency and promoting accountability of government activities. However, it is still not clear how and in what ways blockchain technologies can improve this. This study examines the mechanisms and capability of blockchain technology to contribute to improved transparency and accountability in government. We use a set of system transparency and accountability concepts and mechanisms to critically assess the capabilities of blockchain. By means of a land registration case in Indonesia, we investigate the effects of blockchain on the transparency and accountability of the system. Creating transparency and accountability might be more difficult than expected, as non-technical issues need to be addressed. Based on our assessment we discuss key issues, including digital ID, privacy, interoperability, connectivity and technology aware population, computational efficiency and storage size, acceptability, check and control mechanism, data validity, digital signature, algorithm transparency, law and regulation support, and dispute resolution, that must be considered in developing a transparent and accountable blockchain-based e-Government system.
Public procurement relies in an apparent irreconcilability between competition, which implies some confidentiality, and transparency. The latest Public Procurement Directives have made e-procurement a mandatory feature. Since blockchain technology has been developed and designed to accomplish integrity, transparency, efficiency and data accuracy, goals which are very much appreciated in public procurement, an interesting question then arises: is there room to apply this technology within public procurement procedures? Will smart contracts be an interesting tool within public procurement? Considering public duties such as data protection, which must be complied with by contracting authorities, and some blockchain features such as non-withdrawable information and the likely broad access to the information there enclosed, one can be drawn to conclude that there is no possible conciliation between these two procedures. The mandatory e-procurement implies some neighbouring problems with this technology. Yet, are there any technological solutions for some of the drawbacks?
As the adoption of blockchain technology increases, those wanting to leverage it will need to consider some of the legal challenges under GDPR. The aim of this article is to explore the unique characteristics of blockchain and to identify some of the issues that might arise under GDPR when implementing this technology in an interactive entertainment context.
Due to the advantages of blockchain technologies, including decentralization, immutability, transparency and security, people try to replace existing problematic architectures /frameworks with blockchain based ones. In this paper we propose a novel authentication and authorization framework based on blockchain technologies to control access to the resources of an IoT device. In this paper, we focus on devices such as the Cyber Handyman used in remote collaboration applications to develop our framework. We tested our smart contracts on the Ropsten test network. Our results showed that it can handle 25 service requests simultaneously.
Under the phrase “code is law” and based on its “trustless trust”, blockchain has emerged as a disrupting technology considered by some as an alternative to the law. Based on a study of real-life blockchain-based decentralised applications (Dapps), this article takes blockchain developers at their word and adopts the point of view of users: can blockchain live up to its promise and enable them to transact with each other without the need for the trust granted by the law? The article particularly highlights that users need to be able to ascertain that a self-advertised Dapp indeed qualifies as one. Blockchain technology may make it possible to do away with trust in third parties, but this is not enough. Users also need to trust that an alleged Dapp genuinely is one, and blockchain alone cannot provide this. Beyond Dapps, it is argued that blockchain needs the complementary role of the law to deliver its promises and especially to authenticate blockchain “virtues”. The EU certification mark is identified as a promising form of co-regulation for that purpose.
Mobile crowdsensing(MCS) is an emerging pattern which means task initiators attract mobile users sensing with their own devices by some platforms. MCS could exploit idle resources in low cost, while it has lots of flaws, which impede its developments. First, isolations between different MCS systems leads to wastage of social resources. What's more, current MCS always operate in a centralized way, which causes it vulnerable and unbelievable. Blockchain is a promising technology which could supply a credible and transparent environment. This paper construct a blockchain based MCS market and design smart contract for its operation. In our design, platform breaks isolation by blockchain, task initiators and mobile users manage their tasks by smart contract and bargain price with distributed algorithm. By this way, resource could be exploited better, and the market could be more fair. What's more, the paper analyzes Walrasian Equilibrium (WE) in the market, and details how to deploy MCS in blockchain. Evalution results shows that Equilibrium could be found.
Recent years has witnessed a boom in fog-assisted crowdsensing, which exploits powerful sensing capabilities of various mobile devices or vehicles distributed in large-scale areas to efficiently gather information and make better decisions. However, the fog-assisted crowdsensing system is totally open, which provides the opportunity for malicious individuals or organizations to launch different attacks. In order to cope with the security threats from participants, a blockchain-based crowdsensing framework is proposed, which helps check the authentication of submitted sensor data and resists record tempering. Moreover, a bitcoin-based reward delivery scheme is designed to prevent requesters from denying payments. The sensing capability differences between users are considered in our design. Through security analysis and simulations evaluation, the performance superiority of the proposed framework and reward delivery scheme is demonstrated, in terms of malicious behaviour detection, user utility and sensor data quality.
We present and evaluate models that allow clients to access IoT resources using secure and trusted device-to-device (D2D) communication, while utilizing smart contracts to obtain the benefits of blockchain technology. These benefits include decentralized trust, immutability, transparency, and high availability. The models consider different network connection capabilities of the clients and the IoT resources, namely continuous network connectivity and D2D-only connectivity. We describe two approaches for utilizing blockchains and smart contracts in the authorization process: in the first approach, only hashes of the authorization information are recorded on the blockchain. In the second approach, a smart contract handles authorization requests. We implement the approaches using the OAuth 2.0 delegated authorization framework and evaluate the implementations on the public Ethereum testnet Rinkeby, in terms of execution cost, contract creation cost, and delay. Our evaluation quantifies the tradeoffs of blockchain cost and smart contract functionality, such as blocking and non-blocking operation, and the reduction of the transaction cost that can be achieved when multiple authorization requests are concatenated in a single transaction.
Biometrics have been used increasingly heavily for identity authentication in many critical public services, such as border passes or security check points. However, traditional biometrics-based identity management systems collect and store personal biometrical data in a centralized server or database, and an individual has no control over how her biometrics will be used for what purpose. Such kind of systems can result in serious security and privacy issues for sensitive personal data. In this paper, we design a novel approach to leveraging biometrics and blockchain/smart contract to enable secure and privacy preserving identity management. The basic idea is to use blockchain to store an authority's attestation and the transformed value of an individual's biometrics. The stored data on the blockchain is then controlled by smart contracts which define various access control policies, e.g., access parties, access times, etc. The owner of the biometrical data can flexibly change the access control policies through a white list, a timer and other methods to any identity verifiers. We used the well-known Ethereum platform to implement the proposed approach and tested the effectiveness as well as the flexibility of various access control policies.
Jian An, Yang He, Xiaolin Gui, Wendong Zhang · 6 authors
With the rapid growth of smart terminals in recent years, crowdsensing which utilizes the human intelligence to solve complicated problems have gained considerable interest and exploit. The majority of the existing crowdsensing systems rely on a trusted third-party platform to complete sensing tasks and collect large-scale data. However, the platform cannot completely ensure trust in the real world. The issues of security and privacy caused by the center platform should not be ignored. In this paper, we propose a decentralized privacy-preserving model based on twice verifications and consensuses of blockchain (TCNS). In the prototype of TCNS, an anonymity strategy which can be verified based on the elliptic curve algorithm is proposed to protect the user identity privacy. Then, we propose a twice consensus mechanism, which ensures that the data can be traced and avoids data from being impersonated, tampered with, and denied. Moreover, we propose a user attribute protection scheme based on the lightweight homomorphic encryption algorithm. Finally, considering various influencing factors comprehensively, TCNS uses fuzzy theories to select the candidate mobile nodes. Further, we implement the prototype with real-world datasets, the experimental analysis of privacy protection and safety shows that TCNS can effectively prevent association analysis attacks and background knowledge attacks. More gratifying, the time overhead for generating a new block is acceptable.