Blockchain Papers

Mengmeng Yang, Tianqing Zhu, Kaitai Liang, Wanlei Zhou · 5 authors

No abstract is available for this record.

Bing Jia, Tao Zhou, Wuyungerile Li, Zhenchang Liu · 5 authors

Crowd sensing is a perception mode that recruits mobile device users to complete tasks such as data collection and cloud computing. For the cloud computing platform, crowd sensing can not only enable users to collaborate to complete large-scale awareness tasks but also provide users for types, social attributes, and other information for the cloud platform. In order to improve the effectiveness of crowd sensing, many incentive mechanisms have been proposed. Common incentives are monetary reward, entertainment & gamification, social relation, and virtual credit. However, there are rare incentives based on privacy protection basically. In this paper, we proposed a mixed incentive mechanism which combined privacy protection and virtual credit called a blockchain-based location privacy protection incentive mechanism in crowd sensing networks. Its network structure can be divided into three parts which are intelligence crowd sensing networks, confusion mechanism, and blockchain. We conducted the experiments in the campus environment and the results shows that the incentive mechanism proposed in this paper has the efficacious effect in stimulating user participation.

Ella Tallyn, Larissa Pschetz, Rory Gianni, Chris Speed · 5 authors

Technologies such as distributed ledgers and smart contracts are enabling the emergence of new autonomous systems, and providing enhanced systems to track the provenance of goods. A growing body of work in HCI is exploring the novel challenges of these systems, but there has been little attention paid to their impact on everyday activities. This paper presents a study carried out in 3 office environments for a 1-month period, which explored the impact of an autonomous coffee machine on the everyday activity of coffee consumption. The Bitbarista mediates coffee consumption through autonomous processes, presenting provenance data at the time of purchase while attempting to reduce intermediaries in the coffee trade. Through the report of interactions with and around the Bitbarista, we explore its implications for everyday life, and wider social structures and values. We conclude by offering recommendations for the design of community shared autonomous systems.

Yazan Boshmaf, Husam Al Jawaheri, Mashael Al Sabah

Annotating blockchains with auxiliary data is useful for many applications. For example, e-crime investigations of illegal Tor hidden services, such as Silk Road, often involve linking Bitcoin addresses, from which money is sent or received, to user accounts and related online activities. We present BlockTag, an open-source tagging system for blockchains that facilitates such tasks. We describe BlockTag's design and present three analyses that illustrate its capabilities in the context of privacy research and law enforcement.

Shaohan Feng, Wenbo Wang, Dusit Niyato, Dong In Kim · 5 authors

With the explosive growth of smart IoT devices at the edge of the Internet, embedding sensors on mobile devices for massive data collection and collective environment sensing has been envisioned as a cost-effective solution for IoT applications. However, existing IoT platforms and framework rely on dedicated middleware for (semi-) centralized task dispatching, data storage and incentive provision. Consequently, they are usually expensive to deploy, have limited adaptability to diverse requirements, and face a series of data security and privacy issues. In this paper, we employ permissionless blockchains to construct a purely decentralized platform for data storage and trading in a wireless-powered IoT crowdsensing system. In the system, IoT sensors use the power wirelessly transferred from RF-energy beacons for data sensing and transmission to an access point. The data is then forwarded to the blockchain for distributed ledger services, i.e., data/transaction verification, recording, and maintenance. Due to the coupled interference of wireless transmission and the transaction fee incurred by the blockchain's distributed ledger services, rational sensors have to decide on their transmission rates to maximize their individual payoff. Thus, we formulate a noncooperative game model to analyze this competitive situation among the sensors. We provide the analytical condition for the existence of the Nash equilibria as well as a series of insightful numerical results about the equilibrium strategies in the game.

Dimitris Chatzopoulos, Sujit Gujar, Boi Faltings, Pan Hui

The popularity and applicability of mobile crowdsensing applications are continuously increasing due to the widespread of mobile devices and their sensing and processing capabilities. However, we need to offer appropriate incentives to the mobile users who contribute their resources and preserve their privacy. Blockchain technologies enable semi-anonymous multi-party interactions and can be utilized in crowdsensing applications to maintain the privacy of the mobile users while ensuring first-rate crowdsensed data. In this work, we propose to use blockchain technologies and smart contracts to orchestrate the interactions between mobile crowdsensing providers and mobile users for the case of spatial crowdsensing, where mobile users need to be at specific locations to perform the tasks. Smart contracts, by operating as processes that are executed on the blockchain, are used to preserve users' privacy and make payments. Furthermore, for the assignment of the crowdsensing tasks to the mobile users, we design a truthful, cost-optimal auction that minimizes the payments from the crowdsensing providers to the mobile users. Extensive experimental results show that the proposed privacy preserving auction outperforms state-of-the-art proposals regarding cost by ten times for high numbers of mobile users and tasks.

Volker Strobel, Eduardo Castelló Ferrer, Marco Dorigo

While swarm robotics systems are often claimed to be highly fault-tolerant, so far research has limited its attention to safe laboratory settings and has virtually ignored security issues in the presence of Byzantine robots---i.e., robots with arbitrarily faulty or malicious behavior. However, in many applications one or more Byzantine robots may suffice to let current swarm coordination mechanisms fail with unpredictable or disastrous outcomes. In this paper, we provide a proof-of-concept for managing security issues in swarm robotics systems via blockchain technology. Our approach uses decentralized programs executed via blockchain technology (blockchain-based smart contracts) to establish secure swarm coordination mechanisms and to identify and exclude Byzantine swarm members. We studied the performance of our blockchain-based approach in a collective decision-making scenario both in the presence and absence of Byzantine robots and compared our results to those obtained with an existing collective decision approach. The results show a clear advantage of the blockchain approach when Byzantine robots are part of the swarm.

Marcin Płóciennik, Mario Drobics, Ivana Podnar Žarko, Konstantinos V. Katsaros · 6 authors

In the current Internet of Things (IoT), centralized IoT structures greatly limit the direct, efficient and privacy preserving interaction with the locally available resources. A sustainable path for the future development of Smart Urban Environments, from Smart Homes and Offices, to Smart Neighborhoods and Cities, requires next-generation IoT solutions which are interoperable and decentralized. Building on direct device-to-device interactions and the existing infrastructure operated by open and interoperable platforms, a novel decentralized IoT architecture is required to offer both privacy-preserving and smart real-time interactions in Smart Spaces, leading thus to truly trustful ambient intelligence serving ordinary citizens in everyday situations. We present the key interoperability and security-related aspects which are designed and implemented within the H2020 project symbIoTe to pave the way for such decentralized IoT solutions. Furthermore, we analyze the requirements and technologies, namely Distributed Ledger Technology (DLT), intelligent agents and edge technologies, as the building blocks for the next-generation IoT solutions.

Chris Elsden, John Vines

In this position paper we discuss the methodological challenges associated with engaging citizens, publics and research participants in speculations around future socio-technical systems. We focus on distributed autonomous organizations and associated smart contracting and distributed ledger technologies as an example of such systems. Drawing on our prior work on Speculative Enactments, we highlight the potential value of speculative approaches to engaging people in the design of DAOs that (i) have clear consequentiality for participants, (ii) illustrate scenarios of the future mundane involving these technologies, and (iii) give opportunities for participants to co-construct speculations. We suggest these as provocative starting points to conducting future participatory and speculative design research on DAOs, and to promote discussion with workshop attendees.

Yutao Jiao, Ping Wang, Dusit Niyato, Kongrath Suankaewmanee

As an emerging decentralized secure data management platform, blockchain has gained much popularity recently. To maintain a canonical state of blockchain data record, proof-of-work based consensus protocols provide the nodes, referred to as miners, in the network with incentives for confirming new block of transactions through a process of “block mining” by solving a cryptographic puzzle. Under the circumstance of limited local computing resources, e.g., mobile devices, it is natural for rational miners, i.e., consensus nodes, to offload computational tasks for proof of work to the cloud/fog computing servers. Therefore, we focus on the trading between the cloud/fog computing service provider and miners, and propose an auction-based market model for efficient computing resource allocation. In particular, we consider a proof-of-work based blockchain network, which is constrained by the computing resource and deployed as an infrastructure for decentralized data management applications. Due to the competition among miners in the blockchain network, the allocative externalities are particularly taken into account when designing the auction mechanisms. Specifically, we consider two bidding schemes: the constant-demand scheme where each miner bids for a fixed quantity of resources, and the multi-demand scheme where the miners can submit their preferable demands and bids. For the constant-demand bidding scheme, we propose an auction mechanism that achieves optimal social welfare. In the multi-demand bidding scheme, the social welfare maximization problem is NP-hard. Therefore, we design an approximate algorithm which guarantees the truthfulness, individual rationality and computational efficiency. Through extensive simulations, we show that our proposed auction mechanisms with the two bidding schemes can efficiently maximize the social welfare of the blockchain network and provide effective strategies for the cloud/fog computing service provider.

Flávio Codeço Coelho

Abstract Disease surveillance, especially for infectious diseases, is a complex and inefficient process. Here we propose an optimized, blockchain-based monitoring and reporting process which can achieve all the desired features of an ideal surveillance system while maintaining costs down and being transparent and robust. We describe the technical specifications of such a solution and discuss possibilities for its implementation. Finally, the impact of the adoption of distributed ledger technology for disease surveillance is discussed.

Yuan Lu, Qiang Tang, Guiling Wang

We design and implement the first private and anonymous decentralized crowdsourcing system ZebraLancer, and overcome two fundamental challenges of decentralizing crowdsourcing, i.e., data leakage and identity breach. First, our outsource-then-prove methodology resolves the tension between the blockchain transparency and the data confidentiality to guarantee the basic utilities/fairness requirements of data crowdsourcing, thus ensuring: (i) a requester will not pay more than what data deserve, according to a policy announced when her task is published via the blockchain; (ii) each worker indeed gets a payment based on the policy, if he submits data to the blockchain; (iii) the above properties are realized not only without a central arbiter, but also without leaking the data to the open blockchain. Second, the transparency of blockchain allows one to infer private information about workers and requesters through their participation history. Simply enabling anonymity is seemingly attempting but will allow malicious workers to submit multiple times to reap rewards. ZebraLancer also overcomes this problem by allowing anonymous requests/submissions without sacrificing accountability. The idea behind is a subtle linkability: if a worker submits twice to a task, anyone can link the submissions, or else he stays anonymous and unlinkable across tasks. To realize this delicate linkability, we put forward a novel cryptographic concept, i.e., the common-prefix-linkable anonymous authentication. We remark the new anonymous authentication scheme might be of independent interest. Finally, we implement our protocol for a common image annotation task and deploy it in a test net of Ethereum. The experiment results show the applicability of our protocol atop the existing real-world blockchain.

Atin Angrish, Benjamin Craver, Mahmud Hasan, Binil Starly

With product customization an emerging business opportunity, organizations must find ways to collaborate and enable sharing of information in an inherently trust-less network. In this paper, we propose – “FabRec”: a decentralized approach to handle manufacturing information generated by various organizations using blockchain technology. We propose a system in which a decentralized network of manufacturing machines and computing nodes can enable automated transparency of an organization’s capability, third party verification of such capability through a trail of past historic events and automated mechanisms to drive paperless contracts between participants using ‘smart contracts’. Our system decentralizes critical information about the manufacturer and makes it available on a peer-to-peer network composed of fiduciary nodes to ensure transparency and data provenance through a verifiable audit trail. We present a testbed platform through a combination of manufacturing machines, system-on-chip platforms and computing nodes to demonstrate mechanisms through which a consortium of disparate organizations can communicate through a decentralized network. Our prototype testbed demonstrates the value of computer code residing on a decentralized network for verification of information on the blockchain and ways in which actions can be autonomously initiated in the physical world. This paper intends to expose system elements in preparation for much larger field tests through the working prototype and discusses the future potential of blockchain for manufacturing IT.

Jing-Zhong Wang, Mengru Li, Yunhua He, Hong Li · 6 authors

Crowdsensing applications utilize the pervasive smartphone users to collect large-scale sensing data efficiently. The quality of sensing data depends on the participation of highly skilled users. To motivate these skilled users to participate, they should receive enough rewards for compensating their resource consumption. Available incentive mechanisms mainly consider the truthfulness of the mechanism, but mostly ignore the issues of security and privacy caused by a “trustful” center. In this paper, we propose a privacy-preserving blockchain incentive mechanism in crowdsensing applications, in which a cryptocurrency built on blockchains is used as a secure incentive way. High quality contributors will get their payments that are recorded in transaction blocks. The miners will verify the transaction according to the sensing data assessment criteria published by the server. As the transaction information can disclose users’ privacy, a node cooperation verification approach is proposed to achieve$k$-anonymity privacy protection. Through theoretical analysis and simulation experiments, we show the feasibility and security of our incentive mechanism.

Xueqin Liang, Zheng Yan

A number of information and resource sharing systems arise and become popular with the rapid development of communication technologies and mobile smart devices. The interactions between humans and machines are intense and their synergistic reactions have attracted special attention for the reason of forming so called Human–Machine Networks (HMN). HMNs refer to these networks where humans and machines work together to provide synergistic effects on their payoffs. Game theory, which can capture the interactions among players dexterously, has been widely used in solving various problems in HMN systems from the view of economics. In this paper, we extensively review the literature about game theoretical methods in HMNs, in particular focusing on its typical systems such as crowdsourcing, an elemental HMN and Internet of Things (IoT), a hybrid HMN, as well as Bitcoin. We propose a series of requirements to evaluate existing work. For reviewing and analyzing each system, we specify application purposes, players, strategies, game models and equilibria based on our proposed requirements. In the sequel, we identify a number of common and distinct open issues in HMNs and point out future research directions.

Haoyan Wu, Zhijie Li, Brian King, Zina Ben Miled · 6 authors

Supply chains (SC) span many geographies, modes and industries and involve several phases where data flows in both directions from suppliers, manufacturers, distributors, retailers, to customers. This data flow is necessary to support critical business decisions that may impact product cost and market share. Current SC information systems are unable to provide validated, pseudo real-time shipment tracking during the distribution phase. This information is available from a single source, often the carrier, and is shared with other stakeholders on an as-needed basis. This paper introduces an independent, crowd-validated, online shipment tracking framework that complements current enterprise-based SC management solutions. The proposed framework consists of a set of private distributed ledgers and a single blockchain public ledger. Each private ledger allows the private sharing of custody events among the trading partners in a given shipment. Privacy is necessary, for example, when trading high-end products or chemical and pharmaceutical products. The second type of ledger is a blockchain public ledger. It consists of the hash code of each private event in addition to monitoring events. The latter provide an independently validated immutable record of the pseudo real-time geolocation status of the shipment from a large number of sources using commuters-sourcing.

Anton Muehlemann

The wisdom of the crowd is a valuable asset in today’s society. It is not only important in predicting elections but also plays an essential role in marketing and the financial industry. Having a trustworthy source of opinion can make forecasts more accurate and markets predictable. Until now, a fundamental problem of surveys is the lack of incentives for participants to provide accurate information. Classical solutions like small monetary rewards or the chance of winning a prize are often not very attractive for participants. More attractive solutions, such as prediction markets, face the issue of illegality and are often unavailable. In this work, we present a solution that unites the advantages from classical polling and prediction markets via a customizable incentivization framework. Apart from predicting events, this framework can also be used to govern decentralized autonomous organizations.

Yutao Jiao, Ping Wang, Dusit Niyato, Zehui Xiong

Blockchain, an emerging decentralized security system, has been applied in many applications, such as bitcoin, smart grid, and Internet-of-Things. However, running the mining process may cost too much energy consumption and computing resource usage on handheld devices, which restricts the use of blockchain in mobile environments. In this paper, we consider deploying edge computing service to support the mobile blockchain. We propose an auction-based edge computing resource market of the edge computing service provider. Since there is competition among miners, the allocative externalities (positive and negative) are taken into account in the model. In our auction mechanism, we maximize the social welfare while guaranteeing the truthfulness, individual rationality and computational efficiency. Based on blockchain mining experiment results, we define a hash power function that characterizes the probability of successfully mining a block. Through extensive simulations, we evaluate the performance of our auction mechanism which shows that our edge computing resources market model can efficiently solve the social welfare maximization problem for the edge computing service provider.

Ben Fisch, Rafael Pass, Abhi Shelat

Mining for Bitcoins is a high-risk high-reward activity. Miners, seeking to reduce their variance and earn steadier rewards, collaborate in pooling strategies where they jointly mine for Bitcoins. Whenever some pool participant is successful, the earned rewards are appropriately split among all pool participants. Currently a dozen of different pooling strategies (i.e., methods for distributing the rewards) are in use for Bitcoin mining. We here propose a formal model of utility and social welfare for Bitcoin mining (and analogous mining systems) based on the theory of discounted expected utility, and next study pooling strategies that maximize the social welfare of miners. Our main result shows that one of the pooling strategies actually employed in practice--the so-called geometric pay pool--achieves the optimal steady-state utility for miners when its parameters are set appropriately. Our results apply not only to Bitcoin mining pools, but any other form of pooled mining or crowdsourcing computations where the participants engage in repeated random trials towards a common goal, and where "partial" solutions can be efficiently verified.

Vinod K. Tiwari, Vijay Kumar Singh

Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein, sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fuelled by the recent adaptation of a variety of enabling wireless technologies such as RFID tags and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a Cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A Cloud implementation using Aneka, which is based on interaction of private and public Clouds is presented. We conclude our IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.

Matthias Stuermer, Gabriel Abu-Tayeh, Thomas Myrach

The modern age has heralded a shift from the industrial society, in which natural resources are crucial input factors for the economy, towards a knowledge society. To date, sustainability literature has treated knowledge-and in particular digital artifacts-mainly as a means to the end of achieving sustainable development. In this conceptual paper, we argue that digital artifacts themselves ought also to be considered as resources, which also need to be sustainable. While over-consumption is a problem facing natural resources, with sustainable digital artifacts, underproduction, and underuse are the biggest challenges. In our view, the sustainability of digital artifacts improves their potential impact on sustainable development. A theoretical foundation for digital artifacts and their ecosystem allows us to present the relevant research on digital information, knowledge management, digital goods, and innovation literature. Based on these insights, we propose ten basic conditions for sustainable digital artifacts and their ecosystem to ensure that they provide the greatest possible benefit for sustainable development. We then apply those characteristics to four exemplary cases: Linux kernel development, Bitcoin cryptocurrency, the Wikipedia project, and the Linking Open Drug Data repositories. The paper concludes with a research agenda identifying topics for sustainability scholars and information systems academics, as well as practitioners. A number of suggestions for future studies on digital sustainability are also put forward.

Sergi Delgado-Segura, Cristian Tanas, Jordi Herrera‐Joancomartí

In Mobile Crowd Sensing (MCS), the power of the crowd, jointly with the sensing capabilities of the smartphones they wear, provides a new paradigm for data sensing. Scenarios involving user behavior or those that rely on user mobility are examples where standard sensor networks may not be suitable, and MCS provides an interesting solution. However, including human participation in sensing tasks presents numerous and unique research challenges. In this paper, we analyze three of the most important: user participation, data sensing quality and user anonymity. We tackle the three as a whole, since all of them are strongly correlated. As a result, we present PaySense, a general framework that incentivizes user participation and provides a mechanism to validate the quality of collected data based on the users' reputation. All such features are performed in a privacy-preserving way by using the Bitcoin cryptocurrency. Rather than a theoretical one, our framework has been implemented, and it is ready to be deployed and complement any existing MCS system.

Michael Strasser, Şahin Albayrak

The Internet of Things and Services (IoTS) has encouraged the development of service provisioning systems in respect to Smart City topics. Most of them are operated as heterogeneous systems which limits end customers’ access and contradicts with IoTS principles. In this paper, we discuss and develop a reference model of an interconnected service marketplace ecosystem. The prototypical implementation incorporates findings from an empirical study and lessons learned from research projects. The elaborated ecosystem enables service request roaming between different parties across system boundaries. The paper presents a feasible centralized architecture, introduces involved parties and parts of a developed message protocol. Why a contracting mechanism is indispensable for request roaming is also outlined. The model’s feasibility is demonstrated by means of a current electric mobility use case: providing access to foreign charging infrastructure without multiple registrations. This work contributes to simplify the data exchange between service platforms to improve Smart City solutions and to support travelers with intelligent mobility applications.

Hanieh JavadiKhasraghi, Shahriar Mohammadi

Web2 and the evolving vision of Web3 have a great effect on facilitation of information sharing, information aggregation, interoperability, user-centered design, collaboration on the World Wide Web, and crowd-centered services. New concept of Web is the intuition that drives crowdsourcing, crowd servicing, and crowd computing. With crowdsourcing emergence people get motivated to work through internet without being limited by time or geographical location. On the other hand employers could have their jobs done faster and cheaper. This paper is going to introduce an innovative approach for Amazon Mechanical Turk (AMT) crowdsourcing marketplace. In current AMT marketplace, workers especially new ones need to qualify themselves for each requester that has submitted Human Intelligence Tasks (HITs) in AMT, and there is lack of shared reputation system; some workers may cheat on tasks in order to maximize their income, as a result requesters are uncertain of the quality of results, so they offer lower rewards and consequently qualified workers leave the marketplace.