This paper proposes a trustable mold redesign knowledge-sharing platform, known as CKshare, based on private cloud and blockchain technology. Firstly, we use private cloud to store the mold redesign knowledge of each party to meet its own privacy and data format requirements. Secondly, a blockchain network is used for recording the knowledge and its transactions to ensure security and trustfulness. Thirdly, a simple retrieval mechanism is developed based on k-nearest neighbors for retrieving the codified knowledge on the platform. To realize CKshare, a prototype platform has been developed and explained based on real data from the case mold company.
The recently emerged blockchain (in particular smart contract) technology offers an enticing opportunity for decentralized sharing economy. Machine learning can be one important subroutine in such a decentralized ecosystem. Unfortunately, machine learning programs are usually computational intensive as well as randomized, which fall into the inherent limitations of open blockchain where complex and randomized programs cannot be executed by the underlying nodes collectively. Given also the limitations of existing verifiable computing techniques, we propose a crowdsourcing idea from the game theoretic perspective to resolve the tension. We design a simple incentive mechanism so that the execution of a wide range of complex programs can be crowdsourced via the blockchain, and any false computing result could be deterred. In particular, our protocol works in the scenarios that there is no trusted third-party involved; Moreover, our protocol not only works in the classical model of non-colluding service providers, but also can tolerate any potential coalition up to n-1, where n is the total number of service providers. We also showcase how to use our protocol to crowdsource two typical kinds of machine learning tasks via open blockchain. We envision that our solution is not only promising to launch decentralized applications involving a wide range of machine learning programs, but also a stepping stone towards a general way to empowering intensive and randomized computations atop the open blockchain.
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.
Oct 8, 2018·Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
Danwei Liang, Jian An, Jindong Cheng, Yang He · 5 authors
In most crowdsensing systems, the quality of the collected data is varied and difficult to evaluate while the existing crowdsensing quality control methods are mostly based on a central platform, which is not completely trusted in reality and results in fraud and other problems. To solve these questions, a novel crowdsensing quality control model is proposed in this paper. First, the idea of blockchain is introduced into this model. The credit-based verifier selection mechanism and twice consensuses are proposed to realize the non-repudiation and non-tampering of information in crowdsensing. Then, the quality grading evaluation (QGE) is put forward, in which the method of truth discovery and the idea of fuzzy theories are combined to evaluate the quality of sensing data, and the garbled circuit is used to ensure that evaluation criteria can not be leaked. Finally, the Experiments show that our model is feasible in time and effective in quality evaluation.
Andreas Martin Seitz, Dominic Henze, Daniel Miehle, Bernd Bruegge · 6 authors
Fog Computing, Augmented Reality (AR) and Blockchain are technologies that have been receiving more attention in recent years. Fog Computing for on-site data analysis and Blockchain as a decentralized framework are used to establish security and trust. AR enables new interactive scenarios with devices in the industrial environment and provides user interfaces for devices that had previously lacked one. The combination of these technologies in an industrial environment opens up new possibilities and opportunities. We present the IIoT Bazaar, a decentralized marketplace for industrial edge applications that relies on Blockchain to create transparency for all stakeholders involved and to enable the traceability of app installations on edge devices. With Fog Computing, resource-limited edge devices can be integrated into the IIoT Bazaar ecosystem. Fog Nodes enable the provisioning of applications on edge devices and their integration into a decentralized Blockchain network. AR serves as an interface between the users and the machines, allowing people to interact intuitively with the edge devices. With a case study, we demonstrate the design and prototypical implementation of the IIoT Bazaar and its applications which bring software developers and users together using a combination of Fog Computing, AR, and Blockchain. We share the challenges we faced and our experiences we made during the case study.
Alexander Mikroyannidis, John Domingue, Michelle Bachler, Kevin Quick
Blockchain technology has the potential to revolutionise education in a number of ways. In this paper, we explore the applications of Smart Blockchain Badges on data science education. In particular, we investigate how Smart Blockchain Badges can support learners that want to advance their careers in data science, by offering them personalised recommendations based on their learning achievements. This work aims at enhancing data science accreditation by introducing a robust system based on the Blockchain technology. Learners will benefit from a sophisticated, open and transparent accreditation system, as well as from receiving job recommendations that match their skills and can potentially progress their careers. As a result, this work contributes towards closing the data science skills gap by linking data science education to the industry.
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.
Crowd-sensing systems have gained considerable interests and adoption in recent years. However, most existing crowd-sensing systems rely on central servers, which are subject to low reliability due to the traditional centralized architecture and high service fee. Motivated by constructing a crowd-sensing system with security and low service fee, we propose a blockchain-based crowd-sensing system (BCS), which replaces traditional triangle architecture by decentralized blockchain system. Also, in order to accelerate the formation of the fabric of trust, BCS implements applications of smart contracts to reward sensing-task workers, which offers reliable anonymity in the meantime. By leveraging blockchain technology, BCS has good performance in privacy protection and system robustness.
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.
Jul 1, 2018·2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
Many civil engineering malpractices can be avoided if there are timely, transparent, and unalterable records of these activities. This paper describes an approach to achieve this purpose with blockchain technology. A novel blockchain system designed to avoid high volatility in token price and encourage public participation in maintaining the ledger is introduced. Civil engineering and construction are the first testing fields for the system. It is anticipated that the system, after successfully implemented, can extend its scope to other areas as well.
Leveraging the wisdom of crowd for knowledge discovery and monetization is increasingly popular nowadays. Among others, one popular way of leveraging the crowd wisdom is crowdsensing with truth discovery, which is able to discover truthful knowledge from the unreliable sensory data harvested from mobile clients. In order to become truly successful, however, a number of challenges are yet to be addressed. First, safeguarding clients' sensory data is demanded for privacy protection. Second, in many real crowdsensing applications, data are usually collected in a streaming manner, so truth discovery is naturally required to be efficiently conducted in a streaming fashion. Thirdly, knowledge monetization should be made full-fledged, endowed with features of transparency and streamlined processing while fully addressing the practical needs of parties in the monetization ecosystem. In this paper, we present our initial effort on a crowdsensing framework that enables privacy-preserving knowledge discovery and full-fledged blockchain-based knowledge monetization. Our framework enables privacy-preserving and efficient truth discovery over encrypted crowdsensed data streams for truthful knowledge discovery. Meanwhile, with careful integration of the newly emerging blockchain-based smart contract technology, our framework allows full-fledged knowledge monetization. Tackling the challenges of monetization fairness and (on-chain) knowledge confidentiality, our customized knowledge monetization design well respects the interests of knowledge seller and requester, with full support of transparency, streamlined processing, and automatic quality-aware rewards for clients. Extensive experiments on Microsoft Azure cloud and Ethereum blockchain demonstrate the practically affordable performance of our design.
Mobile peer to peer (P2P) networks offer a huge potential for distributed mobile P2P crowd services (MPCS), which enable data and computational tasks to be offloaded and executed directly between mobile devices. Similar to centralised mobile crowd services, such as mobile crowdsensing, incentivisation mechanisms are core to encouraging mobile users to participate in MPCS systems. However, due to the impact of task execution failures and unreliable behaviours of mobile users (particularly task requesters), it is a daunting task to design and implement an incentivisation mechanism to cater for the needs of MPCS systems. In this paper, we propose a fault-tolerant incentivisation mechanism (FTIM) for MPCS systems. With conditional payment strategies, FTIM is proven to accommodate the requirements of two important application scenarios by achieving mechanism properties such as incentive compatibility, economic efficiency, individual rationality, and weak budget balance. Moreover, to tackle the practical challenges in implementing FTIM in the real world, we design a MPCSTo-ken smart contract to facilitate its service auction, task execution and payment settlement process. We implement the MPCSToken contract on Ethereum blockchain. Both real-world experiment and simulation results show that the system is cost effective for deployments and improves the overall mobile users' utility by exploring the opportunities offered by MPCS.
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 blockchain transparency and data confidentiality, which is critical in crowdsourcing use-case. ZebraLancer ensures: (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. Furthermore, the transparency of blockchain allows one to infer private information about workers and requesters through their participation history. On the other hand, allowing anonymity will enable a malicious worker to submit multiple times to reap rewards. ZebraLancer overcomes this problem by allowing anonymous requests/submissions without sacrificing the 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 with the existing real-world blockchain.
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.
Kapil Singi, D S Pradeepkumar, Vikrant Kaulgud, Sanjay Podder
In this extended abstract, we propose a conceptual framework that leverages distributed ledger technology and smart contracts to create a decentralized system to capture the occurrence of interesting development activities (e.g., a development build) and associated contextual data, and automatically audit and evaluate compliance to governance policies. Our hypothesis is that such a framework will facilitate easier sharing of information across all participants of a distributed development team, compliance evaluation and early mitigation actions, leading to greater visibility and compliance. Currently, the proof of concept we are working on is focused on sharing and compliance evaluation of the open-source components used in software development.
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.
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.
Purpose This paper aims to solve a mining work centralization problem using a gamification-based approach. Design/methodology/approach The authors have developed a simple blockchain application that incorporates a gamification concept into the mining work. Then, they asked some participants in an experiment to use the application for a week and gathered some insights from the responses on questionnaires. Findings The results show that the gamification-based approach distributed mining work among many participants by increasing their motivation to participate mining work. Originality/value The gamification-based approach solves a mining work centralization problem and opens a new direction for future blockchain technologies.
The usage of cell (mobile) phones has increased over the years. As newer and more advanced cellular technology is introduced, the question of what will be done with disposed or retired cell phones becomes a pressing one. Currently, this problem has an impact on the environment, as e-waste in landfills is a growing concern. Many have offered solutions to this problem, some that involve recycling the materials the cell phone is made of or extending the length of the contract so that users keep their cell phones longer. However, in this paper, we provide an alternative to these methods by using our model to determine if a retired cell phone can be repurposed by identifying its functional components and its sensor capabilities. Given this information from our model, a repurpose-capable cell phone can then be used to develop useful smart campus applications and can potentially reduce the number of retired cell phones that become e-waste.
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.
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.