In this paper, the performance evaluation for Internet of Things based on blockchain Technology is proposed. In a blockchain network, all IoT devices communicate and synchronize with each other and allow device to transact with each other directly without the need of trusted intermediary. IoT devices have a smart contract associate with them which are deployed on the blockchain network. User or device who wish to use a service can transact to smart contract that associated with IoT device. Moreover, all transactions of IoT device, device-to device or human-to-device, will not only permanently store on Blockchain network but also gain the security and privacy of them. In this implementation, a private Ethereum network is chosen to use as a blockchain platform and the raspberry pi act as a lightweight node to transact with a smart contract in a full node which install on PC desktop. In addition, the performance evaluation of two realistic traffic flow, store and access transactions, such as latency, execution time and throughput are highlight.
This paper presents a novel way to help match employers' knowledge requirements with students' knowledge earned using blockchain's smart contracts to assure credentials and track student records. This decentralized approach proposes using the micro-accreditation of topics from the CAE framework to courses and associated tasks, while introducing a revolutionary idea of a blockchain-based peer-reviewed rigor score assignment. Our work and result metrics were completed in Ethereum and connected test networks. We concluded this new approach is mostly efficient and scalable depending on the network load, with faster transaction times when the miners are properly incentivized. Future work will include further fine-tuning of the transaction algorithms to improve time, as well as an investigation into a better consensus model for peer review and rigor determination.
Internet of Things (IoT) devices achieve the rapid development and have been widely deployed recently. Meanwhile, inherent vulnerabilities of IoT systems (including firmware and software) have been continually uncovered and thus the systems are always exposed to various attacks. The root cause of the issue is that IoT systems always have design flaws and implementation bugs. In particular, the released systems (e.g., by third-party marketplaces and IoT vendors) may be maliciously repackaged with malware. Unfortunately, IoT consumers are not able to effectively capture such vulnerabilities because of the limited detection capabilities. In this paper, we propose SmartCrowd, a blockchain-based platform that aims to outsource security detection of IoT systems to distributed detectors with strong detection incentives. SmartCrowd enables built-in accountability for IoT providers and authoritative references of detection results for IoT consumers. By building smart contracts, we can incentivize the efficient and high-coverage security detection of IoT systems, while providing decentralized and automated incentives for both IoT providers releasing secure IoT systems and detectors uncovering vulnerabilities. We present the security and theoretical analysis that demonstrates the security of SmartCrowd and the incentives for participators. We prototype SmartCrowd by using Ethereum and the experimental results show that SmartCrowd has both technical feasibility and financial benefits, which can be applied to build a secure IoT ecosystem.
Blockchain is seen as a promising technology to provide reliable and secure services due to its decentralized characteristic. However, because of the limited throughput, current blockchain platforms can not meet the transaction demand in practical use. Though researchers proposed many new solutions, they suffered either decentralization or security issues. In this paper, using Directed Acyclic Graph (DAG) structure, we improve the linear structure of traditional blockchain protocol. In the new structure, blocks are organized in levels and width, which will generate into a compacted DAG structure (CoDAG). To make CoDAG more efficient and secure, we design algorithms and protocols to place the new-generated blocks appropriately. Compared with traditional blockchain protocols, CoDAG improves the security and transaction verification time, and enjoys the consistency and liveness properties of blockchain. Taking adversary parties into consideration, two possible attack strategies are presented in this paper, and we further prove that CoDAG is a secure and robust protocol to resist them. The experimental results show that CoDAG can achieve 394 transactions per second, which is 56 times of Bitcoin's throughput and 26 times of Ethereum's.
Alen Hrga, Federico-Matteo Bencic, Ivana Podnar Žarko
Initial Coin Offering (ICO) is a process similar to crowdfunding, in which companies raise funds from investors, who in return receive tokens or digital assets. With conventional methods of crowdfunding, the level of transparency depends on a centralized platform used in campaigns. With the emergence of peer-to-peer digital currency systems, also known as cryptocurrencies, it became possible to implement crowdfunding campaigns in a fully transparent way for investors. Public sales of blockchain digital assets are known as crowdsales which are implemented using blockchain smart contracts. The paper presents a solution for automating ICO processes implemented using the Ethereum blockchain and explain the basics of crowdsale token sale flow. Next, we analyze features vital for transparent ICO execution as well as the benefits and costs of running an ICO on cryptocurrency application platforms.
Samvid Dharanikota, Michael Jensen, Sebastian Rom Kristensen, Mathias Sass Michno · 7 authors
Randomness beacons are services that periodically emit a random number, allowing users to base decisions on the same random value without trusting anyone: ideally, the randomness beacon does not only produce unpredictable values, but is also of low computational complexity for the users, bias-resistant and publicly verifiable. Such randomness beacons can serve as an important primitive for smart contracts in a variety of contexts. This paper first presents a structured security analysis, based on which we then design, implement, and evaluate a trustworthy and efficient randomness beacon. Our approach does not require users to register or run any computationally intensive operations. We then compare different implementation and deployment options on distributed ledgers, and report on an Ethereum smart contract-based lottery using our beacon.
Internet of Things (IoT) as per estimated will connect 50 billion devices by 2020. Since its evolution, IoT technology provides lots of flexibility to develop and implement any application. Most of the application improves the human living standard and also makes life easy to access and monitoring the things in real time. Though there exist some security and privacy issues in IoT system like authentication, computation, data modification, trust among users. In this paper, we have identified the IoT application like insurance, supply chain system, smart city and smart car where trust among associated users is an major issue. The current centralized system does not provide enough trust between users. Using Blockchain technology we have shown that trust issue among users can be managed in a decentralized way so that information can be traceable and identify/verify any time. Blockchain has properties like distributed, digitally share and immutable which enhance security. For Blockchain implementation, Ethereum platform is used.
Ana Lidia Franzoni Velázquez, Cristina Cardenas, Alejandro Almazan
Blockchain has the potential to transform the financial services industry, institutional functions, business operations, and other areas such as education. The current paper focuses on one real-world illustration of Blockchain's potential - a pilot project that used a Blockchain (hosted by Ethereum) to store certifications for 1,518 teachers who participated in a teacher training in Mexico.
When a Solidity smart contract has a problem in calling a function of another contract, the "fallback function" of the contract is supposed to be executed automatically. However, in many cases, a fallback function is arbitrarily created and called, with their behaviors unknown to developers, so that its execution is vulnerable to exploits by attackers. To reduce these risks, this paper proposes a method that provides developers with new keywords by modifying existing Solidity compiler and Ethereum Virtual Machine (EVM). Developers mark their intention using the newly introduced keywords, and the modified existing Solidity compiler and EVM uses flags and conditional statements to prevent calls of fallback functions to reduce the risk of calls to fallback functions.
Access control technology is an important information security mechanism. At present, most of the database systems and enterprise information systems are role-based access control technologies, this rights management system has been running stably. However, due to the simple role access control, its flexibility and control granularity sometimes can't meet the requirements of actual access control. This paper proposes a secure access control model ARBACV1 based on RBACV1 combined with ABAC model, which is more flexible than RBACV1 and can perform fine-grained access control. The open transparency of data in the blockchain has caused people's high attention to data privacy protection issues[1]. A complete access control mechanism has not been provided in the Ethereum blockchain. To this end, according to the blockchain architecture, the proposed access control model ARBACV1 is applied to the blockchain through smart contracts, and the access of the blockchain users is controlled securely, and the code is written in Solidity language in Ethereum[2]. ARBACV1-based access control is implemented in blockchain.
Ride sharing is a centralized trust based system where users trust the service providers for the ride set up, tracking, cancellation, fare calculation etc. Any malicious activity in the centralized server based system or driver or rider destroys the fairness involved in the ride and causes inconvenience to the parties. After the completion of the ride, the drivers are rated by the riders. There are possibilities that, a malicious rider can claim the refund with a fake complain and give the driver poor rating. Current system is not capable of deciding the correctness of the objections raised by either parties and provides a biased outcome of each objections as per the centralized company's marketing strategies. We present BlockV, a blockchain enabled solution to ensure the fairness of the ride. The creation, completion, dissatisfaction or abortion of any ride will be written in the blockchain ledger, hence will be available to all participants in the peer to peer network. This simultaneously ensures the fairness in maintenance of the inbuilt reputation system. We have implemented a prototype in Ethereum private network and KOVAN test network and the analysis is included.
Electronic Health Records have proven to be indispensable yet continue to present a host of problems. One of the most pressing concerns is how to share patient information freely and efficiently. Hospitals and clinics may share data internally, but there is an inability due to the lack of infrastructure or an unwillingness to share data between systems. Implementing a peer-to-peer distributed digital ledger, known as a blockchain, to record and transmit transactional data in conjunction with Cloud based technologies may be a solution to bridge the communication gap. This paper sets forth a new approach for a blockchain and cloud computing network utilizing Amazon Web Services and Ethereum blockchain to facilitate semantic level interoperability of Electronic Health Records systems without standardized data forms and formatting.
Each of the most popular blockchain platform, Bitcoin, Ethereum, and Hyperledger Fabric, varies in aspects of decentralization, permission, anonymity, and native-currency, has its own consensus mechanism, algorithm and implementation. In the mainstream blockchain technology, there are many common consensus algorithms. They differ in terms of computational complexity, fault-tolerance, and resilience. The performance, consistency, scalability, and efficiency of blockchain consensus mechanism need further improvement and optimization. Consensus mechanism and code implementation of Bitcoin, Ethereum and Hyperledger are analyzed, discussed and proposed.
Blockchain has recently emerged as an important tool that can enable critical distributed applications without requiring centralized trust. For example, public blockchains have been used to enable many different cryptocurrencies. Unfortunately, existing public blockchains and smart contracts deployed on them may disclose sensitive information. Although there is some ongoing work that leverage advanced cryptography to address some of these sensitive information leakage issues, they require significant changes to existing and popular blockchains such as Ethereum and are usually computationally expensive. On the other hand, private blockchains have been proposed to allow more efficient and privacy-preserving data sharing among pre-approved group of nodes/participants. Although private blockchains address some of the privacy challenges by allowing sensitive data to be only seen by the select group of participants, they do not allow public accountability of transactions since transactions are approved by known set of users, and cannot be accessed publicly. Given these observations, one natural question that arise is, can we leverage both public and private blockchain infrastructures to enable efficient, privacy enhancing and accountable applications? In this work, we try to address this challenge in the context of digital auctions. Mainly, we propose a novel hybrid blockchain architecture that combines private and public blockchains to allow sensitive bids to be opened on a private blockchain so that only the auctioneer can learn the bids, and no one else. At the same time, we leverage public blockchains to make the auction winner announcement, and payments accountable. Furthermore, using smart contracts deployed on public blockchain, we show how to incentivize truthful behavior among the auction participants. Our extensive empirical results show that this architecture is more efficient in terms of run time and monetary cost compared to pure public blockchain based auction implementations.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Social media signals have been successfully used to develop large-scale predictive and anticipatory analytics. For example, forecasting stock market prices and influenza outbreaks. Recently, social data has been explored to forecast price fluctuations of cryptocurrencies, which are a novel disruptive technology with significant political and economic implications. In this paper we leverage and contrast the predictive power of social signals, specifically user behavior and communication patterns, from multiple social platforms GitHub and Reddit to forecast prices for three cyptocurrencies with high developer and community interest - Bitcoin, Ethereum, and Monero. We evaluate the performance of neural network models that rely on long short-term memory units (LSTMs) trained on historical price data and social data against price only LSTMs and baseline autoregressive integrated moving average (ARIMA) models, commonly used to predict stock prices. Our results not only demonstrate that social signals reduce error when forecasting daily coin price, but also show that the language used in comments within the official communities on Reddit (r/Bitcoin, r/Ethereum, and r/Monero) are the best predictors overall. We observe that models are more accurate in forecasting price one day ahead for Bitcoin (4% root mean squared percent error) compared to Ethereum (7%) and Monero (8%).
As data marketplaces are becoming common place, it is also becoming clear that data streams generated from Internet of Things (IoT) devices hold value for potential third party consumers. We envision a marketplace for IoT data streams that can unlock such potential value in a scalable way, by enabling any pairs of data providers and consumers to engage in data exchange transactions without any prior assumption of mutual trust. We present a marketplace model and architecture to support trading of streaming data, from the advertising of data assets to the stipulation of legally binding trading agreements, to their fulfilment and payment settlement. Crucially, we show that by using blockchain technology and Smart Contracts in particular, we can offer participants a trade-off between the cost of transactional data exchange, and the risk of data loss when trading with untrusted third parties. We experimentally assess such trade-offs on a testbed using Ethereum Smart Contracts.
Recently blockchain technology has attracted increasing attention. It provides a distributed peer-to-peer network. It also allows to enlarge the contracting space using smart contracts. Smart contract is a numeric protocol which define a promises between parties. In a blockchain platform, we can find millions of smart contracts which are created by different users (developers). The smarts contracts created by users and saved in a blockchain can be similar in functionality, even if different users use different wording. This paper presents a new search engine in the blockchain. The novelty of our search engine is to help users to checks their smart contracts by referencing some similar existing smart contracts created and saved in a blockchain platform. Our search engine allows to give each user an adaptive set of similar smart-contracts based on the user's similarity needs. Our search engine is developed in the Ethereum blockchain platform. Experiments demonstrate the potential of our search engine system under different scenarios.
Decentralization is a key selling point of most public blockchain platforms. However, despite the widely acknowledged importance of this property, most researches on this topic lack quantification, and none of them performs a calculation on the degrees of decentralization they achieve in practice. In this paper, taking Bitcoin and Ethereum for instances, we propose an entropy method in information theory to quantify the decentralization for them. Using the information entropy, we calculate the discrete degrees of blocks mined and address balances to quantify the degrees of decentralization for Bitcoin and Ethereum systems, and the results of calculations indicate that Bitcoin's mining is more approximately 12% decentralized than Ethereum with full samples, and Bitcoin's wealth is more approximately 9.2% decentralized than Ethereum with 10,000 samples. Our method can be used to evaluate the degree of decentralization for any blockchain system.
The importance and usage of the distributed cloud is increasing rapidly over a traditionally centralized cloud for the storing and exchanging of digital assets between untrusted parties in many business sectors. Storing the digital assets in the distributed cloud is considered superior to traditional cloud computing in terms of environmentally friendly, cost, security and other technical dimensions. In this article, a contemporary architecture DistProv is proposed where an open source distributed cloud IPFS is used to store and transfer the digital assets between the consignor and consignee. These two are untrusted parties exchanging sensitive documents secured by cryptographic algorithms with permission-based access verified by ethereum smart contracts using zero-knowledge proof (ZKP) and simultaneously publishing the provenance data about the digital asset as a transaction on the blockchain. This article also discusses on verifying the integrity of the digital assets and authentication of the consignor and thus preserving a strong CIA triad.
Online voting is an alternative to age old paper ballot system and the currently popular electronic voting machines (EVM). An electronic voting portal should offer security and integrity along with the transparency of votes and privacy of voters. This paper proposes an e-voting system based on blockchain that eliminates some of the limitations in existing voting systems. The paper also presents state of art of some blockchain frameworks for e-voting. The presented implementation is suitable for small scale elections like inside corporate houses, board rooms etc. The implementation uses smart contract from Ethereum. Truffle framework is used in this paper for development, testing and deploying smart contracts. Ganache is used as Ethereum client for testing. Here Meta-mask is used as browser wallet.
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Blockchain technology has positively impacted traceability across various industries such as logistics and shipping. By overcoming the problem of data silos among organizations and concentration of authority, this innovative approach allows a decentralized and tamper-resistant ledger to be built. On the other hand, the use of non-fungible tokens, a new concept for projecting digital and physical goods on a blockchain, is expected to be able to represent complicated operations in traceability systems. However, the existing token design lacks an efficient model for retrieval of past histories. The most popular way to retrieve past information on tokens is to use blockchain explorers, which are centralized trusted parties. Otherwise, so far there is only a naive way to examine all block headers, and it takes a vast amount of time. Our preliminary study shows that the processing time for retrieving all histories of 1,030 tokens on the Ethereum mainnet takes approximately 57 minutes. We propose a new token design based on a directed acyclic graph (DAG) that allows token histories to be efficiently explored without examining the whole blockchain. The model associates each state of the token from past to latest and covers expressions of relationships between tokens, such as merge and split. Our implementation and evaluation reveal that the DAG-based token design significantly improves the efficiency of exploring token transfer histories. The results show that our method can complete the exploration for 1,030 tokens in a matter of seconds and maintains performance over the long term even if the blockchain grows.
Blockchain technology platform Ethereum (open-source platform) has rapidly evolved and provides interfaces that allow users to develop variety of Blockchain applications using its "Solidity" programming language. Due to its security and privacy, and smart contract execution capabilities, Ethereum became a favorite option for banking and other application domains. In this paper, we investigate the feasibility of Ethereum capabilities for online Supply Chain systems in Business-to-Consumer (B2C) business model. This work aims to research Ethereum platform capabilities and language, including smart contracts and their advantages over regular contracts. We develop illustrative application to demonstrate smart contracts in the B2C Supply Chain system. The application demonstrates the role of a smart contracts in executing order transactions, from placing an order to receiving the shipment. Furthermore, we add to the application a third component to track and update shipping information between suppliers and consumers.
The emerging blockchain technology, powered by the smart contract functionality, is expected to revolutionize traditional systems by decentralization and autonomy. When the blockchain technology is applied in real-life systems, a smart contract may need to take in sensitive data to execute its code. For example, a decentralized medical insurance smart contract needs access to personal health data. Therefore, it is crucial to guarantee both privacy and authenticity of data sent to the smart contract, so that everyone can verify data without leaking sensitive information. Currently, only few works have tried to achieve privacy and authenticity at the same time. In this work, we first propose zk-DASNARK, a zero-knowledge SNARK scheme for authenticated data. It is designed by combining the zk-SNARK technique with digital signature in an effective way. Based on zk-DASNARK, we design zk-AuthFeed, a zero-knowledge authenticated data feed scheme to achieve both data privacy and authenticity for smart contract. We implement zk-AuthFeed and conduct comprehensive experiments on Ethereum. The experiments show that zk-AuthFeed is highly efficient: key generation takes about 7 seconds only, proof generation takes less than 2 seconds, and proof verification takes less than 40 ms.
Machine learning has recently enabled large advances in artificial intelligence, but these tend to be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published models can quickly become out of date without effort to acquire more data and re-train them. We propose a framework for participants to collaboratively build a dataset and use smart contracts to host a continuously updated model. This model will be shared publicly on a blockchain where it can be free to use for inference. Ideal learning problems include scenarios where a model is used many times for similar input such as personal assistants, playing games, recommender systems, etc. In order to maintain the model's accuracy with respect to some test set we propose both financial and non-financial (gamified) incentive structures for providing good data. A free and open source implementation for the Ethereum blockchain is provided at https://github.com/microsoft/0xDeCA10B.