Purpose The transaction process of an office building is known to be time consuming and inefficient, in part due to the lack of market transparency. The purpose of this paper is to focus on the development of a blockchain application that can improve the transaction process of office buildings in the Netherlands. Design/methodology/approach Conducting design science research, the current transaction process of an office building and status quo of blockchain technology in real estate is investigated. Subsequently, multiple parties are interviewed to define major pain points within the process. The interview findings are used to design a blockchain solution which overcomes the aforementioned pain points. After designing, the interviewees are asked again to pragmatically validate the proposed model. Findings One of the major pain points identified concerning the transaction process of an office building is that it is difficult to define the characteristics of a property, due to lack of data structure and quality. The proposed application improves the way specific assets are understood by structuring physical and contractual information in one place and guarantees the quality of the data by using the blockchain mechanisms. Practical implications A blockchain application is proposed, which can improve the transaction process of an office building. Originality/value Recent studies indicate that blockchain technology could lead to improvements in efficiency, transparency and therefore trust within the transaction process. Therefore, the proposed application is of value for the future of real estate data management and the transaction process.
Purpose The application of smart contract can greatly reduce transaction costs and improve transaction efficiency. The existing smart contract are expensive, single application scenario and inefficient. This paper aims to propose a new smart contract model to solve these problems. Design/methodology/approach By investigating the research history, models and platforms, this paper summarizes the shortcomings of existing smart contracts. Based on the content and architecture of traditional contract, a smart contract model with wider application scope is designed. Findings In this paper, several models are used to describe the operation mechanism of smart contracts. To facilitate computer execution, a decomposition method is proposed, which divides smart contracts into several sub-contracts. Then, the advantages and deployment methods of smart contract are discussed. On this basis, a specific example is given to illustrate how the application of smart contract will change our life. Originality/value Smart contract is gradually applied to more fields. In this paper, the structure and operation mechanism of smart contract system in reality are given, which will be beneficial to the application of smart contract to more complex systems.
Johannes Eckert, David López, Carlos Lima Azevedo, Bilal Farooq
Since the transport sector accounts for one of the highest shares of greenhouse gases (GHG) emissions, several existing proposals state the idea to control the by the transportation sector caused GHG emissions through an Emission Trading Systems (ETS). However, most existing approaches integrate GHG emissions through the fuel consumption and car registration, limiting the tracing of emissions in more complex modes e.g. shared vehicles, shared rides and even public transportation. This paper presents a new design of a user-centric ETS and its implementation as a carbon Blockchain framework for Smart Mobility Data-market (cBSMD). The cBSMD allows for the seamless transactions of token-equivalent GHG emissions when realizing a trip, or an emission trading action as well as the transaction of individual, service or system-wide emission performance data. We demonstrate an instance of the cBSMD implementation for the transactions of an ETS where all travellers receive a certain amount of emission credits in the form of tokens, linked to the GHG price and a total emission cap. Travellers use their tokens each time they emit GHG when travelling in a multi-modal network, purchase tokens for a given trip when they have an insufficient token amount or sell when having a surplus of tokens due to a lower amount of emitted GHG. This instance of cBSMD is then applied to a case-study of 24hours of mobility of 3,186 travellers from Oakville, Ontario, Canada, where we showcase different cBSMD transactions and analyze token usage and emission performance.
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne
\n\t\t\t\t\tBlockchain technology with its secure, transparent and decentralized nature has been recently employed in many mobile applications. However, the process of executing extensive tasks such as computation-intensive data applications and blockchain mining requires high computational and storage capability of mobile devices, which would hinder blockchain applications in mobile systems. To meet this challenge, we propose a mobile edge computing (MEC) based blockchain network where multi-mobile users (MUs) act as miners to offload their data processing tasks and mining tasks to a nearby MEC server via wireless channels. Specially, we formulate task offloading, user privacy preservation and mining profit as a joint optimization problem which is modelled as a Markov decision process, where our objective is to minimize the long-term system offloading utility and maximize the privacy levels for all blockchain users. We first propose a reinforcement learning (RL)-based offloading scheme which enables MUs to make optimal offloading decisions based on blockchain transaction states, wireless channel qualities between MUs and MEC server and user’s power hash states. To further improve the offloading performances for larger-scale blockchain scenarios, we then develop a deep RL algorithm by using deep Q-network which can efficiently solve large state space without any prior knowledge of the system dynamics. Experiment and simulation results show that the proposed RL-based offloading schemes significantly enhance user privacy, and reduce the energy consumption as well as computation latency with minimum offloading costs in comparison with the benchmark offloading schemes.\n\t\t\t\t
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne
For current and future Internet of Things (IoT) networks, mobile edge-cloud computation offloading (MECCO) has been regarded as a promising means to support delay-sensitive IoT applications. However, offloading mobile tasks to the cloud gives rise to new security issues due to malicious mobile devices (MDs). How to implement offloading to alleviate computation burdens at MDs while guaranteeing high security in mobile edge cloud is a challenging problem. In this paper, we investigate simultaneously the security and computation offloading problems in a multi-user MECCO system with blockchain. First, to improve the offloading security, we propose a trustworthy access control mechanism using blockchain, which can protect cloud resources against illegal offloading behaviours. Then, to tackle the computation management of the authorized MDs, we formulate a computation offloading problem by jointly optimizing the offloading decisions, the allocation of computing resource and radio bandwidth, and smart contract usage. This optimization problem aims to minimize the long-term system costs of latency, energy consumption and smart contract fee among all MDs. To solve the proposed offloading problem, we develop an advanced deep reinforcement learning algorithm using a double-dueling Q-network. Evaluation results from real experiments and numerical simulations demonstrate the significant advantages of our scheme over the existing approaches.
Despite being described as a medium of exchange, cryptocurrencies do not have the typical attributes of a medium of exchange. Consequently, cryptocurrencies are more appropriately described as crypto assets. A common investment attribute shared by the more than 2,500 crypto assets is that they are highly volatile. An investor interested in reducing price volatility of a portfolio of crypto assets can do so by constructing an optimal portfolio through standard optimization techniques that minimize tail risk. Because crypto assets are not backed by any real assets, forming a hedge to reduce the risk contribution of a single crypto asset can only be done with another set of similar assets (i.e., a set of other crypto assets). A major finding of this paper is that crypto portfolios constructed via optimizations that minimize variance and Conditional Value at Risk outperform a major stock market index (the S$\&$P 500). As of this writing, options in which the underlying is a crypto asset index are not traded, one of the reasons being that the academic literature has not formulated an acceptable fair pricing model. We offer a fair valuation model for crypto asset options based on a dynamic pricing model for the underlying crypto assets. The model was carefully backtested and therefore offers a reliable model for the underlying crypto assets in the natural world. We then obtain the valuation of crypto options by passing the natural world to the equivalent martingale measure via the Esscher transform. Because of the absence of traded crypto options we could not compare the prices obtained from our valuation model to market prices. Yet, we can claim that if such options on crypto assets are introduced, they should follow closely our theoretical prices after adjusting for market frictions and design feature nuances.
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne
For current and future Internet of Things (IoT) networks, mobile edge-cloud\ncomputation offloading (MECCO) has been regarded as a promising means to\nsupport delay-sensitive IoT applications. However, offloading mobile tasks to\nthe cloud is vulnerable to security issues due to malicious mobile devices\n(MDs). How to implement offloading to alleviate computation burdens at MDs\nwhile guaranteeing high security in mobile edge cloud is a challenging problem.\nIn this paper, we investigate simultaneously the security and computation\noffloading problems in a multi-user MECCO system with blockchain. First, to\nimprove the offloading security, we propose a trustworthy access control using\nblockchain, which can protect cloud resources against illegal offloading\nbehaviours. Then, to tackle the computation management of authorized MDs, we\nformulate a computation offloading problem by jointly optimizing the offloading\ndecisions, the allocation of computing resource and radio bandwidth, and smart\ncontract usage. This optimization problem aims to minimize the long-term system\ncosts of latency, energy consumption and smart contract fee among all MDs. To\nsolve the proposed offloading problem, we develop an advanced deep\nreinforcement learning algorithm using a double-dueling Q-network. Evaluation\nresults from real experiments and numerical simulations demonstrate the\nsignificant advantages of our scheme over existing approaches.\n
Internet of things (IoT) is becoming increasingly important and ubiquitous in home and industries. It makes object a part of the Internet and fuses the digital and physical world together. However, if not properly secured, IoT device can be vulnerable to tampering that can change the content of the data stored in the network. Blockchain, a technology used in cryptocurrency, can be used for addressing the security and privacy challenges in IoT. Blockchain can be beneficial to IoT by adding more security layer and reducing dependency on a central authority. This paper proposed to develop a blockchain based platform for IoT application. Blockchain technology can be utilized to provide a decentralized network, creating a more secured IoT system. The proposed blockchain network will be based on Ethereum blockchain network allowing the use smart contract application for management of IoT devices. Experiment is conducted to show the feasibility of the blockchain based platform. The proposed blockchain based platform is capable of managing several IoT devices connected to the network.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Domenico Rotondi, Marco Saltarella, Gaetano Giordano, Francesco Pellecchia
Abstract Compliance of distributed ledger technology (DLT) based solutions with the European Union General Data Protection Regulation (EU GDPR) is currently a hot topic both from a technical point of view, as well as from a legal and normative one. Flexible working is a new working model where employees can perform their work activity without specific time and space constraints. In this context privacy and information trustworthiness are relevant and, therefore, on the one hand it can gain benefit from using DLT based solutions, on the other hand it must comply with the GDPR. This paper describes a solution that combines DLTs and the new Ciphertext‐Policy Attribute Based Encryption cryptographic techniques to support compliance with the EU GDPR in the context of flexible working. The devised solution is being concretely experimented, in the context of the EU H2020 CITADEL project, by the Municipality of Bari (Italy).
Adam Gągol, Damian Leśniak, Damian Straszak, Michał Świętek
The spectacular success of Bitcoin and Blockchain Technology in recent years has provided enough evidence that a widespread adoption of a common cryptocurrency system is not merely a distant vision, but a scenario that might come true in the near future. However, the presence of Bitcoin's obvious shortcomings such as excessive electricity consumption, unsatisfying transaction throughput, and large validation time (latency) makes it clear that a new, more efficient system is needed. We propose a protocol in which a set of nodes maintains and updates a linear ordering of transactions that are being submitted by users. Virtually every cryptocurrency system has such a protocol at its core, and it is the efficiency of this protocol that determines the overall throughput and latency of the system. We develop our protocol on the grounds of the well-established field of Asynchronous Byzantine Fault Tolerant (ABFT) systems. This allows us to formally reason about correctness, efficiency, and security in the strictest possible model, and thus convincingly prove the overall robustness of our solution. Our protocol improves upon the state-of-the-art HoneyBadgerBFT by Miller et al. by reducing the asymptotic latency while matching the optimal communication complexity. Furthermore, in contrast to the above, our protocol does not require a trusted dealer thanks to a novel implementation of a trustless ABFT Randomness Beacon.
Machine learning algorithms learn from data and use data from databases that are mutable; therefore, the data and the results of machine learning cannot be fully trusted. Also, the machine learning process is often difficult to automate. A unified analytical framework for trustable machine learning has been presented in the literature. It proposed building a trustable machine learning system by using blockchain technology, which can store data in a permanent and immutable way. In addition, smart contracts on blockchain are used to automate the machine learning process. In the proposed framework, a core machine learning algorithm can have three implementations: server layer implementation, streaming layer implementation, and smart contract implementation. However, there are still open questions. First, the streaming layer usually deploys on edge devices and therefore has limited memory and computing power. How can we run machine learning on the streaming layer? Second, most data that are stored on blockchain are financial transactions, for which fraud detection is often needed. However, in some applications, training data are hard to obtain. Can we build good machine learning models to do fraud detection with limited training data? These questions motivated this paper; which makes two contributions. First, it proposes training a machine learning model on the server layer and saving the model with a special binary data format. Then, the streaming layer can take this blob of binary data as input and score incoming data online. The blob of binary data is very compact and can be deployed on edge devices. Second, the paper presents a new method of synthetic data generation that can enrich the training data set. Experiments show that this synthetic data generation is very effective in applications such as fraud detection in financial data.
Driven by the increasing number of stationary and portable devices, Distributed Denial-of-Service (DDoS) attacks pose a major threat to Internet availability. While advantages of cooperative defenses have been widely recognized over traditional on-premise defenses, there is not a widespread deployment of such cooperative defenses. This work demonstrates the Blockchain Signaling System (BloSS), a modular, network-agnostic and cooperative DDoS defense system consisting of independent instances working together to mitigate attacks targeted at any member of this alliance.
Cryptocurrency investigations have centered almost entirely around the transfer of value “money” or a cryptocurrency asset. The use of cryptocurrency for illicit purposes, especially Bitcoin, is well documented both in academic writing, media reporting and even film documentaries. The infamous SilkRoad market place in addition to the millions of dollars spent within dark markets on drugs, guns and assassinations have grabbed the headlines. This paper looks at how blockchain is creating new areas of investigation that are yet to be explored in detail. This scenario-based research examines the hosting of stolen data (P.I.I) personal identifiable information on a distributed blockchain host where the data is also accessible. The platform used is based on Ethereum infrastructure but demonstrates just one available platform that poses the paradigm. The paper examines the considerations through the lens of an incident responder /cyber investigator, forensics examiner and data controller. The scenario highlights distinct differences in considerations from a traditional response compared to dealing with the immutable and unstoppable distributed technology. The paper concludes that more is needed to be done to understand digital forensics in the blockchain era and the need to develop beyond track and trace in the cryptocurrency investigative tool box. The discussion also brings forth how data retention and GDPR requires consideration when applying it blockchain systems.
A primary concern of a wireless sensor network (WSN) is to gather data from the immediate environment of it sensors while minimizing the use of limited network and computational resources. Several studies have focused on how to efficiently store and process sensed data in WSN. Generally, the appropriate method to store sensed data depends on the application for which the WSN was deployed. No matter the application, data collection appears to be a primary function of a WSN. The execution of this function must be coordinated and effective in order to provide WSN with current security standards such as privacy, data integrity and end entity authentication between communicating peers. In this paper, we propose an efficient authentication-based security scheme for data retrieval in WSN. This security scheme combines zero-knowledge proofs (ZKP) and pre-shared key method to provide secured and authenticated communication during data retrieval by a mobile sink in WSN. The security mechanism proposed works on a clustered network topology with an index-based data dissemination scheme. The network employs the concept of Connected Dominating Set (CDS) to form storage and index node sets. Upon a successful peer authentication, the index, located on the index node, is used for efficient retrieval of data. The scheme also provides end-to-end confidentiality given that data is being encrypted before transferred and can be decrypted only at the base station. Security and performance analysis of the proposed scheme show that it addresses all of the aforementioned issues while also satisfying zero-knowledge proofs properties. It is also suitable for devices with limited computational resources as the network can fulfil the purpose of data collection and can be deployed in large-scale wireless sensor networks.
Damiano Di Francesco Maesa, Andrea Marino, Laura Ricci
The availability of the entire Bitcoin transaction history, stored in its public blockchain, offers interesting opportunities for analysing the transaction graph to obtain insight on users behaviour. This paper presents an analysis of the Bitcoin users graph, obtained by clustering the transaction graph, to highlight its connectivity structure and the economical meaning of the different obtained components. In fact, the bow tie structure, already observed for the graph of the web, is augmented, in the Bitocoin users graph, with the economical information about the entities involved. We study the connectivity components of the users graph individually, to infer their macroscopic contribution to the whole economy. We define and evaluate a set of measures of nodes inside each component to characterize and quantify such a contribution. We also perform a temporal analysis of the evolution of the resulting bow tie structure. Our findings confirm our hypothesis on the components semantic, defined in terms of their economical role in the flow of value inside the graph.
Stefano Angieri, Alberto García-Martínez, Bingyang Liu, Zhiwei Yan · 6 authors
The current system to manage the global pool of IP addresses is centralized in five transnational organizations, known as regional internet registries (RIRs). Each of them manages the address pool for many countries. In this paper, we present InBlock, a distributed autonomous organization that provides the decentralized management of IP addresses. The InBlock also fulfills the same objectives as those fulfilled by the current IP address allocation organizations, i.e., uniqueness, fairness, conservation, aggregation, registration, and minimized overhead. The InBlock is implemented as a set of blockchain's smart contracts in Ethereum, and it implements all the functions needed for the management of a global pool of addresses without any human intervention. Any entity may request an allocation of addresses to the InBlock registry by performing a (crypto)currency transfer to the InBlock. The fee required, along with the annual renewal fee, serves as a mechanism to deter stockpiling and other wasteful practices. As with any novel technology, there are many open questions about the usage of blockchains to build an IP address registry. For this reason, we believe that practical experimentation is required in order to have hands-on experience, so we propose to conduct an experiment on the InBlock as a starting point to inform about the future directions in this space.
The design of access control mechanisms for healthcare systems is challenging: it must strike the right balance between permissions and restrictions. In this work, we propose a novel approach that is based on the Blockchain technology for storage patient medical data and create an audit logging system able to protect health data from unauthorized modification and access. The proposed method consists of a tree structure: a main chain linked with the patient's identity and one or several Subchains which are used for storing additional critical data (e.g., medical diagnoses or access logs).
Stefano Bistarelli, Ivan Mercanti, Francesco Santini
In Bitcoin, the most common kind of transactions is in the form “Bob pays Alice”, and it is based on the Pay to-Public Key Hash(P2PKH) script, which are resolved by sending the public key and a digital signature created by the corresponding private key. P2PKH transactions are just one among many standard classes: a transaction is standard if it passes Bitcoin Core’s IsStandard() and IsStandardTx() tests. However, the creation of ad-hoc scripts to lock (and unlock) transactions allows for also generating non-standard transactions, which can be nevertheless broadcast and mined as well. In this work, we explore the Bitcoin block-chain with the purpose to analyze and classify standard and non-standard transactions, understanding how much the standard behaviour is respected.
Huashan Chen, Marcus Pendleton, Laurent Njilla, Shouhuai Xu
The blockchain technology is believed by many to be a game changer in many application domains, especially financial applications. While the first generation of blockchain technology (i.e., Blockchain 1.0) is almost exclusively used for cryptocurrency purposes, the second generation (i.e., Blockchain 2.0), as represented by Ethereum, is an open and decentralized platform enabling a new paradigm of computing --- Decentralized Applications (DApps) running on top of blockchains. The rich applications and semantics of DApps inevitably introduce many security vulnerabilities, which have no counterparts in pure cryptocurrency systems like Bitcoin. Since Ethereum is a new, yet complex, system, it is imperative to have a systematic and comprehensive understanding on its security from a holistic perspective, which is unavailable. To the best of our knowledge, the present survey, which can also be used as a tutorial, fills this void. In particular, we systematize three aspects of Ethereum systems security: vulnerabilities, attacks, and defenses. We draw insights into, among other things, vulnerability root causes, attack consequences, and defense capabilities, which shed light on future research directions.
Bitcoin and Ethereum, whose miners arguably collectively comprise the most powerful computational resource in the history of mankind, offer no more power for processing and verifying transactions than a typical smart phone. The system described herein bypasses this bottleneck and brings scalable computation to Ethereum. Our new system consists of a financial incentive layer atop a dispute resolution layer where the latter takes form of a versatile "verification game." In addition to secure outsourced computation, immediate applications include decentralized mining pools whose operator is an Ethereum smart contract, a cryptocurrency with scalable transaction throughput, and a trustless means for transferring currency between disjoint cryptocurrency systems.
Blockchain technology has the potential to change the way corporations are managed and how they function. A system that offers greater decentralization and ability for shareholders to more actively and accurately engage in decision-making processes will be fundamental for modern corporate governance. We observe that shareholders in recent years have become more active and interested in corporate matters of the companies that they have invested. Decades after Berle & Means elemental publication, the division between the investment and control pertains. Often, because of the existing architecture of the system. Yet, the architecture is changing and blockchain represents a new component. Shareholders could thanks to the technological development strengthen their voice and be part of the long-term corporate decisions. Could technology be the answer to the long-lasting division between corporations and their investors as well as the division between investment shareholders and retail shareholder? If we organized a corporation and its information and decision-making mechanisms based on a new technology that promotes collaboration and can easily encompass incentive mechanisms, we might have a tool to provide more efficiency and transparency and even potentially address the values (or a lack of them) that today govern of our corporate system. This article provides an analysis on opportunities and potential challenges of using blockchain for the purposes of corporate governance in publicly traded corporation. Beside the inquiry into the technology behind blockchain, the article reflects the value, if any, the blockchain technology would have for the shareholders and suggests how the technology could be used in publicly traded companies.