The paper discusses the possibility of combining RFID and Blockchain technology to more effectively prevent counterfeiting of products or raw materials, and to solve problems related to production, logistics and storage. Linking these technologies can lead to better planning by increasing the transparency and traceability of industrial or logistical processes or such as efficient detection of critical chain sites.
The appearance and rapid development of cryptocurrencies put into operation new terms such us "blockchain", "distributed ledger" and "smart contract". The possibilities for application of blockchain technology are stretching far beyond the territory of the cryptocurrencies. The financial industry is among the sectors where the new technology is expected to cause dramatic changes. The focus of the analysis of this paper is on the following issues: what blockchain technology and smart contracts are, and in which segments of the financial markets could they find a favorable ground for application and development? The research methodology is based on literature review and secondary data which present the foundation for answering the following questions: how realistic the boom forecasts are in the blockchain application and what is the nature of the expected changes - will they lead to the end of the domination of the financial institutions-mastodons or there will be a new evolutionary phase in their development?
Ricardo Carreño, Verónica Aguilar-Esteva, Daniel Pacheco, Antonio Acevedo · 6 authors
Knowledge society blockchain is one of the most powerful and recent tools to make the internet environment safer and reliable. Manufacturing has traditionally been dominated by standard designs that are mass-produced, due to the fact, that custom production causes additional costs that make it less affordable than mass production. This paper proposes to develop a designer expert system for IoT installation layout designs, using blockchain distributed system based on a machine learning, with users entering data to the expert system by a smart bot software. This expert system will work using extreme learning machine as inference engine; therefore, this is a shell to develop any expert system with fast learning. The whole system is represented by a smart contract with a value linked to the value of the expert system, the more this expert system be quoted on the web, the more the shares of the smart contract will cost.
For various reasons, financial institutions often make use of high-level trading strategies when buying and selling assets. Many individuals, irrespective or their level of prior trading knowledge, have recently entered the field of trading due to the increasing popularity of cryptocurrencies, which offer a low entry barrier for trading. Regardless of the intention or trading strategy of these traders, the invariable outcome is their attempt to buy or sell assets. However, in such a competitive field, experienced market participants seek to exploit any advantage over those who are less experienced, for financial gain. Therefore, this work aims to make a contribution to the important issue of how to optimize the process of buying and selling assets on exchanges, and to do so in a form that is accessible to other traders. This research concerns the optimization of limit order placement within a given time horizon of 100 seconds and how to transpose this process into an end-to-end learning pipeline in the context of reinforcement learning.<br/>Features were constructed from raw market event data that related to movements of the Bitcoin/USD trading pair on the Bittrex cryptocurrency exchange. These features were then used by deep reinforcement learning agents in order to learn a limit order placement policy. To facilitate the implementation of this process, a reinforcement learning environment that emulates a local broker was developed as part of this work. Furthermore, we defined an evaluation procedure which can determine the capabilities and limitations of the policies learned by the reinforcement learning agents and ultimately provides means to quantify the optimization achieved with our approach. Our analysis of the results of this work includes the identification of patterns in cryptocurrency trading that were formed by market participants who posted orders, and a conceptual framework to construct data features containing these patterns. We developed a fully-functioning reinforcement learning environment that emulates a local broker and, by means of this process, we identified which components are essential.<br/>With the use of this environment, we were able to train and test multiple reinforcement learning agents whose aims were to optimize the placement of buy and sell limit orders. During the evaluation, we were able to improve the parameter settings of the constructed reinforcement learning environment and therefore improve the policy learned by the agents. Ultimately, we achieved a significant improvement in limit order placement with the application of a state-of-the-art deep Q-network agent and were able to simulate purchases and sales of 1.0 BTC at a price that was up to $33.89 better than the market price. We have made use of the OpenAI Gym library and contributed our work to the community to enable further investigations to be carried out. The work done in this thesis can be used as a framework to (1) build a component that acts as an intermediary between trader and exchange and (2) to enable exchanges to provide a new order type to be used by traders.
The historic rise of blockchain-based cryptocurrencies to over $327 billion in market capitalization has sparked significant research efforts studying their reliability, performance, and security. Bitcoin, the highest valued cryptocurrency, has received the most thorough scrutiny, with many studies analyzing its peer properties and network health. In contrast, the network layer for Ethereum, the second-largest cryptocurrency, has gone mostly ignored, even though it employs different algorithms for transaction propagation. \n\nIn this thesis, we perform timing analysis on transactions propagated through Ethereum networks to identify the origin nodes. We build a tool called TxSniper to verify our approach on Ethereum's main network. We find that we can identify the origin with a 70% probability; this method is not always effective due to presence of nodes running clients that use different implementations of transaction propagation.
Debiao He, Yudi Zhang, Ding Wang, Kim‐Kwang Raymond Choo
Mobile device and application (app) security are increasingly important, partly due to the constant and fast-paced cyberthreat evolution. To ensure the security of communication (e.g., data-in-transit), a number of identity-based signature schemes have been designed to facilitate authorization identification and validation of messages. However, in many of these schemes, a user's private key may leak when a new signature is generated since the private keys are stored on the device. Seeking to improve the security of the private key, we propose the first two-party distributed signing protocol for the identity-based signature scheme in the IEEE P1363 standard. This protocol requires that two devices separately store one part of the user's private key, and allows these two devices to generate a valid signature without revealing the entire private key of the user. We formally prove that the security of the protocol in the random oracle model. Then, we implement the protocol using the MIRACL library and evaluate the protocol on two mobile devices. Compared with the protocol of Lindell (CRYPTO'17) that uses the zero-knowledge proof for its security, our protocol is more suitable for deployment in the mobile environment.
최근에 ICO(Initial Coin Offering)가 활성화되면서 이더리움 네트워크에 트랜잭션 발생이 짧은 시간에 급증하였고, 그 결과 이더리움의 시간당 거래 처리량이 현저하게 떨어지는 현상이 나타났었다. 본 논문에서는 이러한 현상을 사설 블록체인 환경에서 서로 다른 복잡도를 가진 3가지의 스마트 컨트랙트로 실험하였다. 그 결과, 블록당 트랜잭션의 수가 감소하는 현상을 보이면서 수행속도가 크게 떨어지는 현상이 나타났다. 결과 분석 및 결론에서 성능 저하의 이유를 분석하고, 어떤 스마트 컨트랙트의 특징이 실험 결과에 어떻게 영향을 주었는지 설명한다.
While the smart surveillance system enhanced by the Internet of Things (IoT) technology becomes an essential part of Smart Cities, it also brings new concerns in security of the data. Compared to the traditional surveillance systems that is built following a monolithic architecture to carry out lower level operations, such as monitoring and recording, the modern surveillance systems are expected to support more scalable and decentralized solutions for advanced video stream analysis at the large volumes of distributed edge devices. In addition, the centralized architecture of the conventional surveillance systems is vulnerable to single point of failure and privacy breach owning to the lack of protection to the surveillance feed. This position paper introduces a novel secure smart surveillance system based on microservices architecture and blockchain technology. Encapsulating the video analysis algorithms as various independent microservices not only isolates the video feed from different sectors, but also improve the system availability and robustness by decentralizing the operations. The blockchain technology securely synchronizes the video analysis databases among microservices across surveillance domains, and provides tamper proof of data in the trustless network environment. Smart contract enabled access authorization strategy prevents any unauthorized user from accessing the microservices and offers a scalable, decentralized and fine-grained access control solution for smart surveillance systems.
Pietro Danzi, Anders E. Kalør, Čedomir Stefanović, Petar Popovski
The emerging blockchain protocols provide a decentralized architecture that is suitable of supporting Internet of Things (IoT) interactions. However, keeping a local copy of the blockchain ledger is infeasible for low-power and memory-constrained devices. For this reason, they are equipped with lightweight software implementations that only download the useful data structures, e.g. state of accounts, from the blockchain network, when they are updated. In this paper, we consider and analyze a novel scheme, implemented by the nodes of the blockchain network, which aggregates the blockchain data in periodic updates and further reduces the communication cost of the connected IoT devices. We show that the aggregation period should be selected based on the channel quality, the offered rate, and the statistics of updates of the useful data structures. The results, obtained for the Ethereum protocol, illustrate the benefits of the aggregation scheme in terms of a reduced duty cycle of the device, particularly for low signal-to-noise ratios, and the overall reduction of the amount of information transmitted in downlink (e.g., from the wireless base station to the IoT device). A potential application of the proposed scheme is to let the IoT device request more information than actually needed, hence increasing its privacy, while keeping the communication cost constant. In conclusion, our work is the first to provide rigorous guidelines for the design of lightweight blockchain protocols with wireless connectivity.
Arati Baliga, I Subhod, Pandurang Kamat, Siddhartha Chatterjee
Quorum is a permissioned blockchain platform built from the Ethereum codebase with adaptations to make it a permissioned consortium platform. It is one of the key contenders in the permissioned ledger space. Quorum supports confidentiality and privacy of smart contracts and transactions, and crash and Byzantine fault tolerant consensus algorithms. In this paper, we characterize the performance features of Quorum. We study the throughput and latency characteristics of Quorum with different workloads and consensus algorithms that it supports. Through a suite of micro-benchmarks, we explore how certain transaction and smart contract parameters can affect transaction latencies.
The data science technologies of artificial intelligence (AI), Internet of Things (IoT), big data and behavioral/predictive analytics, and blockchain are poised to revolutionize government and create a new generation of GovTech start-ups. The impact from the ‘smartification’ of public services and the national infrastructure will be much more significant in comparison to any other sector given government’s function and importance to every institution and individual. Potential GovTech systems include Chatbots and intelligent assistants for public engagement, Robo-advisors to support civil servants, real-time management of the national infrastructure using IoT and blockchain, automated compliance/regulation, public records securely stored in blockchain distributed ledgers, online judicial and dispute resolution systems, and laws/statutes encoded as blockchain smart contracts. Government is potentially the major ‘client’ and also ‘public champion’ for these new data technologies. This review paper uses our simple taxonomy of government services to provide an overview of data science automation being deployed by governments world-wide. The goal of this review paper is to encourage the Computer Science community to engage with government to develop these new systems to transform public services and support the work of civil servants.
Constrained devices in IoT networks often require to outsource resource-heavy computations or data processing tasks. Currently, most of those jobs are done in the centralised cloud. However, with rapidly increasing number of devices and amount of produced data, edge computing represents a much more efficient solution decreasing the cost, the delay and improves users' privacy. To enable wide deployment of execution nodes at the edge, the requesting devices require a way to pay for submitted tasks. We present SPOC - a secure payment system for networks where nodes distrust each other. SPOC allows any node to execute tasks, includes result verification and enforce users' proper behaviour without 3rd parties, replication or costly proof of computations. We implement our system using Ethereum Smart Contracts and Intel SGX and present first evaluation proving its security and low usage cost.
In the Internet-of-Things, the number of connected devices is expected to be extremely huge, i.e., more than a couple of ten billion. It is however well-known that the security for the Internet-of-Things is still open problem. In particular, it is difficult to certify the identification of connected devices and to prevent the illegal spoofing. It is because the conventional security technologies have advanced for mainly protecting logical network and not for physical network like the Internet-of-Things. In order to protect the Internet-of-Things with advanced security technologies, we propose a new concept (datachain layer) which is a well-designed combination of physical chip identification and blockchain. With a proposed solution of the physical chip identification, the physical addresses of connected devices are uniquely connected to the logical addresses to be protected by blockchain.
Alexander Mühle, Andreas Grüner, Tatiana Gayvoronskaya, Christoph Meinel
This paper provides an overview of the Self-Sovereign Identity (SSI) concept, focusing on four different components that we identified as essential to the architecture. Self-Sovereign Identity is enabled by the new development of blockchain technology. Through the trustless, decentralised database that is provided by a blockchain, classic Identity Management registration processes can be replaced. We start off by giving a simple overview of blockchain based SSI, introducing an architecture overview as well as relevant actors in such a system. We further distinguish two major approaches, namely the Identifier Registry Model and its extension the Claim Registry Model. Subsequently we discuss identifiers in such a system, presenting past research in the area and current approaches in SSI in the context of Zooko's Triangle. As the user of an SSI has to be linked with his digital identifier we also discuss authentication solutions. Most central to the concept of an SSI are the verifiable claims that are presented to relying parties. Resources in the field are only losely connected. We will provide a more coherent view of verifiable claims in regards to blockchain based SSI and clarify differences in the used terminology. Storage solutions for the verifiable claims, both on- and off-chain, are presented with their advantages and disadvantages.
Information from surveillance video is essential for situational awareness (SAW). Nowadays, a prohibitively large amount of surveillance data is being generated continuously by ubiquitously distributed video sensors. It is very challenging to immediately identify the objects of interest or zoom in suspicious actions from thousands of video frames. Making the big data indexable is critical to tackle this problem. It is ideal to generate pattern indexes in a real-time, on-site manner on the video streaming instead of depending on the batch processing at the cloud centers. The modern edge-fog-cloud computing paradigm allows implementation of time sensitive tasks at the edge of the network. The on-site edge devices collect the information sensed in format of frames and extracts useful features. The near-site fog nodes conduct the contextualization and classification of the features. The remote cloud center is in charge of more data intensive and computing intensive tasks. However, exchanging the index information among devices in different layers raises security concerns where an adversary can capture or tamper with features to mislead the surveillance system. In this paper, a blockchain enabled scheme is proposed to protect the index data through an encrypted secure channel between the edge and fog nodes. It reduces the chance of attacks on the small edge and fog devices. The feasibility of the proposal is validated through intensive experimental analysis.
The present paper attempts to look into the nuances of the direct funding of local government from a vantage point of fiscal federalism in India and also the dynamics of financial decentralization. The reports of finance commissions regarding the devolution of tax powers to local governments in order to make them financially autonomous has been looked into with a incisive constitutional mindset. The impact of centrally sponsored scheme in this regard has been looked into by the researcher in order to get the exposer of current federal implications of the same where the party politics and an attempt to create loyal vote bank is driving the pace of CSS which is affecting the fiscal federalism. The GST has also affected the tax structure of country in many aspects and in paper the impact of it on local government has been contemplated.
Abstract Externalised service provision is now an embedded feature of Australia's service delivery architecture. However, the lessons drawn from two decades of contracted service delivery suggest that “competition” is an imperfect platform for the delivery of public services, especially where issues of trust in government come into play. Could the concept of a “social license to operate” (SLO), which has been in use in the natural resources sector for over two decades, help to facilitate the conferral of greater trust, credibility and legitimacy upon governments, and externalised service providers in social policy spaces?
The public key infrastructure (PKI) based authentication protocol provides the basic security services for vehicular ad-hoc networks (VANETs). However, trust and privacy are still open issues due to the unique characteristics of vehicles. It is crucial for VANETs to prevent internal vehicles from broadcasting forged messages while simultaneously protecting the privacy of each vehicle against tracking attacks. In this paper, we propose a blockchain-based anonymous reputation system (BARS) to break the linkability between real identities and public keys to preserve privacy. The certificate and revocation transparency is implemented efficiently using two blockchains. We design a trust model to improve the trustworthiness of messages relying on the reputation of the sender based on both direct historical interactions and indirect opinions about the sender. Experiments are conducted to evaluate BARS in terms of security and performance and the results show that BARS is able to establish distributed trust management, while protecting the privacy of vehicles.
Michiel Van Beirendonck, Louis-Charles Trudeau, Pascal Giard, Alexios Balatsoukas‐Stimming
Lyra2REv2 is a hashing algorithm that consists of a chain of individual hashing algorithms and it is used as a proof-of-work function in several cryptocurrencies that aim to be ASIC-resistant. The most crucial hashing algorithm in the Lyra2REv2 chain is a specific instance of the general Lyra2 algorithm. In this work we present the first FPGA implementation of the aforementioned instance of Lyra2 and we explain how several properties of the algorithm can be exploited in order to optimize the design.