M. Vijayalakshmi, S. Mercy Shalinie, Ming‐Hour Yang, Shou-Chuan Lai · 5 authors
Supply chain management (SCM) governance is the streamline of the IoT product life cycle from its production to delivery. Integrating blockchain with supply chain management is essential to ensure end-to-end tracking, trustiness between manufacturers and customers, fraud and counterfeit elimination, and customizing administrative costs and paperwork. This paper proposes an RFID ownership transfer protocol with the help of zk-SNARKs (Zero Knowledge-Succinct Noninteractive Arguments of Knowledge) using Ethereum blockchain. When the owner performs RFID transfer, the transferred information will be recorded on the blockchain using smart contracts. When using a smart contract to transfer ownership on the Ethereum blockchain, because the content on the blockchain will not be tampered with, all accounts in the Ethereum can view the transfer results and verify them. The privacy of the supply chain is attained by generating the proof of product code via zk-SNARKs algorithm. This algorithm also enhances the scalability of the supply chain system by creating a trusted setup in off-chain mode.
Open access
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
Objective: Managing training certificates is an important issue in research that can lead to serious issues if not addressed properly. For institutions that currently do not have a dedicated management system for these training certificates, a central database is the most typical solution. However, such a system suffers from several risks, such as a single-point-of-failure. Materials and Methods: To address this issue, we developed and evaluated CertificateChain, a decentralized training certificate management system by using peer-to-peer blockchain and automated smart contracts. We developed an efficient certificate dividing-and-merging algorithm to overcome the transaction size limit on blockchain. Results: We performed experiments on the system to evaluate its performance, then created a web app and tested the system in a real-world scenario. CertificateChain scaled linearly in terms of time compared with the total number of certificates added and could be quickly queried for existing data stored on-chain. Discussion: CertificateChain was able to store and retrieve the training certificates on the blockchain network, with limitations including a comparative analysis of other systems, evaluation of different consensus protocols, examining certificates off-chain, a thorough comparison with a centralized system, and the extension to the main public Ethereum network. Conclusion: We believe that these results indicate that blockchain technology could be a viable decentralized alternative to traditional databases in this use case. Our software is publicly available at: https://doi.org/10.5281/zenodo.6257094.
Jin Ling, Yinzhi Cao, Yan Chen, Di Zhang · 5 authors
Smart contracts, just like other computer programs, are prone to a variety of vulnerabilities, which lead to severe consequences including massive token and coin losses. Prior works have explored automated exploit generation for vulnerable Ethereum contracts. However, the scopes of prior works are limited in both vulnerability types and contract platforms. In this paper, we propose a cross-platform framework, calledExGen, to generate multiple transactions as exploits to given vulnerable smart contracts.ExGenfirst translates either Ethereum or EOS contracts to an intermediate representation (IR). Then,ExGengenerates symbolic attack contracts with transactions in a partial order and then symbolically executes the attack contracts together with the target to find and solve all the constraints. Lastly,ExGenconcretizes all the symbols, generates attack contracts with multiple transactions, and verifies the generated contracts’ exploitability on a private chain with values crawled from the public chain. We implemented a prototype ofExGenand evaluated it on Ethereum and EOS benchmarks.ExGensuccessfully exploits 1,258/1,399 (89.9%) Ethereum and 126/130 (96.9%) EOS vulnerabilities.ExGenis also able to exploit zero-day vulnerabilities on EOS.
Mudassar Hasan, Muhammad Abubakr Naeem, Muhammad Arif, Syed Jawad Hussain Shahzad · 5 authors
We examine the dynamics of liquidity connectedness in the cryptocurrency market. We use the connectedness models of Diebold and Yilmaz (Int J Forecast 28(1):57-66, 2012) and Baruník and Křehlík (J Financ Econom 16(2):271-296, 2018) on a sample of six major cryptocurrencies, namely, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Ripple (XRP), Monero (XMR), and Dash. Our static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies, whereas BTC and LTC play a significant role in connectedness magnitude. A distinct liquidity cluster is observed for BTC, LTC, and XRP, and ETH, XMR, and Dash also form another distinct liquidity cluster. The frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium- and long-run time horizons. In the short run, BTC, LTC, and XRP are the leading contributor to liquidity shocks, whereas, in the long run, ETH assumes this role. Compared with the medium term, a tight liquidity clustering is found in the short and long terms. The time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time, pointing to the possible effect of rising demand and higher acceptability for this unique asset. Furthermore, more pronounced liquidity connectedness patterns are observed over the short and long run, reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time-frequency connectedness.
Cryptocurrencies have become an important element of the global financial system and a frequent investment tool in the last decade. The aim of this paper is to compare the efficiency of investments in the cryptocurrency market with investments in global capital markets. The study used the quotations of the analyzed instruments in the years 2011-2020. The investment efficiency was estimated using Sharpe and Sortino ratios. Research has shown that investments in cryptocurrencies were the most effective. They brought, on average, the highest daily rates of return, but on the other hand, they were characterized by the highest risk. Such a result could have been significantly influenced by the widespread persistence of ultra-low interest rates and a decline in the attractiveness of debt securities. The best results were obtained for investments in bitcoin and ethereum, which have the largest share of cryptocurrency market capitalization.
Smart contracts have been established as the standard mechanism for online crypto-currency transactions in blockchains such as Bitcoin and Ethereum. The application scope of smart contracts is predicted to expand beyond crypto-currency in upcoming years, and this emerging technology is likely to play a significant role in other major domains. Smart contracts are usually created using a special purpose programming language. In this paper, we explore an alternative mechanism based on propositional calculus, using multisignature and lock-based boolean variables. Higher order boolean quantifiers have been avoided, and from a security standpoint, the design is deliberately kept Turing-incomplete to guarantee bounded runtime and well-defined termination paths for any valid smart contract (for homogeneous locks, our validation checks run in linear time for best case and quadratic time for worst case). Keeping in mind a widening scope for smart contracts, the applicability of our design is not confined to blockchain transactions, but can be easily integrated into other application domains.
Abstract Ability to perform fast analysis on massive public blockchain transaction data is needed in various applications such as tracing fraudulent financial transactions. The blockchain data is continuously growing and is organized as a sequence of blocks containing transactions. This organization, however, cannot be used for parallel graph algorithms which need efficient distributed graph data structures. Using message passing libraries (MPI), we develop a scalable cluster-based system that constructs a distributed transaction graph in parallel and implement various transaction analysis algorithms. We report performance results from our system operating on roughly 5 years of 10.2 million block Ethereum Mainnet blockchain data. We report timings obtained from tests involving distributed transaction graph construction, partitioning, page ranking of addresses, degree distribution, token transaction counting, connected components finding and our new parallel blacklisted address trace forest computation algorithm on a 16 node economical cluster set up on the Amazon cloud. Our system is able to construct a distributed graph of 766 million transactions in 218 s and compute the forest of blacklisted address traces in 32 s.
The appealing features of cryptocurrency in the digital money sector have put them into the category of investable assets. Investment professionals have begun to consider their investability and diversification benefits. It is vital for investors to understand the return-risk behaviour among investable assets to reap the benefits of diversification. This paper considers a proxy of cryptos, specifically Bitcoin, Litecoin, Ethereum, Ripple & Neo, and the Middle East stock market indices, to examine the dynamic relationship among them using the vector error correction model. This study found evidence to suggest that cryptos exhibit a co-integrated relationship while there is no evidence of significant cointegrated movements occurring between the cryptos and the market indices. The latter finding implies that cryptos are decoupled from the market indices and can serve as a diversification option for investors. The mean-variance approach confirms that cryptocurrencies fit into an optimal portfolio and involve an enhanced return-risk reward for investors.
As the popularity of e-commerce grows, an electronic coupon (e-coupon) is widely used due to its convenience and portability. In most e-coupon services, the information of e-coupons is managed on a centralized server. However, e-coupon services are often vulnerable to security issues because of centralization. For example, when the e-coupon information which is stored in a centralized e-coupon server is forged, it becomes difficult to match the user and the e-coupon’s owner, and an expired e-coupon can be used repetitively (i.e., double-spending). To handle this issue, we propose a new e-coupon service by exploiting a blockchain system to improve the security of the service. To do this, we first design a server to enable the e-coupon service and communicate with the blockchain system. Second, we devise a smart contract on the blockchain system to provide integrity of the e-coupon business logic and the e-coupon’s information. We implemented the proposed service on an Ethereum-based blockchain system. The experimental results show that our proposed service improves higher security with a minor performance overhead compared with an existing e-coupon service.
The field of blockchain and cryptocurrencies can be both difficult to grasp and improve upon, which makes aids that can assist in these tasks very useful. SpartanGold is a simplified blockchain-based cryptocurrency created at San Jose State University as a learning aid for blockchain and cryptocurrencies. In its current state, it closely resembles Bitcoin, and it is also easily expandable to implement other features. This project extends SpartanGold with a virtual machine resembling the Ethereum Virtual Machine. Implementing this feature results in SpartanGold having Ethereum- related features, which would allow the cryptocurrency to both be a helpful learning aid for Ethereum and be able to solve interesting blockchain problems associated with virtual machines and smart contracts. Using my virtual machine implementation, I was able to produce a simplified token that resembles Ethereum tokens and works with SpartanGold. This token demonstrates the SpartanGold Virtual Machine’s usefulness in simulating smart contracts of real world interest. Going forward, developers can experiment with the SpartanGold Virtual Machine to test out new ideas without dealing with the full complexity of the Ethereum Virtual Machine.
When the Ethereum blockchain was first built, there was no chainId in the blocks. The concept of chainId was introduced after a DAO attack in 2016 that resulted in 3.6 million ethers stolen and made Ethereum blockchain to fork into two blockchains, that is, Ethereum mainnet (ETH) and Ethereum Classic. In this chapter, a crosschain id service project is developed from specification, architecture, design, smart contract coding, to Web client implementations.
David Richter, David Kretzler, Pascal Weisenburger, Guido Salvaneschi · 6 authors
Decentralized applications (dApps) consist of smart contracts that run on blockchains and clients that model collaborating parties. dApps are used to model financial and legal business functionality. Today, contracts and clients are written as separate programs - in different programming languages - communicating via send and receive operations. This makes distributed program flow awkward to express and reason about, increasing the potential for mismatches in the client-contract interface, which can be exploited by malicious clients, potentially leading to huge financial losses. In this paper, we present Prisma, a language for tierless decentralized applications, where the contract and its clients are defined in one unit. Pairs of send and receive actions that "belong together" are encapsulated into a single direct-style operation, which is executed differently by sending and receiving parties. This enables expressing distributed program flow via standard control flow and renders mismatching communication impossible. We prove formally that our compiler preserves program behavior in presence of an attacker controlling the client code. We systematically compare Prisma with mainstream and advanced programming models for dApps and provide empirical evidence for its expressiveness and performance. The design space of dApp programming and other multi-party languages depends on one major choice: a local model versus a global model. In a local model, parties are defined in separate programs and their interactions are encoded via send and receive effects. In a global language, parties are defined within one shared program and interactions are encoded via combined send-and-receive operations with no effects visible to the outside world. The global model is followed by tierless [Christian Queinnec, 2000; Cooper et al., 2007; Choi and Chang, 2019; Fowler et al., 2019; Serrano et al., 2006; Serrano and Prunet, 2016; Radanne et al., 2016; Weisenburger et al., 2018] and choreographic [Kohei Honda et al., 2011; Fabrizio Montesi et al., 2014; Saverio Giallorenzo et al., 2020] languages. However, known approaches to dApp programming follow the local model, thus rely on explicitly specifying the client-contract interaction protocol. Moreover, the contract and clients are implemented in different languages, hence, developers have to master two technology stacks. The dominating approach in industry is Solidity [Mix, 2019] for the contract and JavaScript for clients. Solidity relies on expressing the protocol using assertions in the contract code, which are checked at run time [Solidity documentation - common patterns, 2020]. Failing to insert the correct assertions may give parties illegal access to monetary values to the detriment of others [Nikolić et al., 2018; Luu et al., 2016]. In research, contract languages [Ankush Das et al., 2019; Michael J. Coblenz, 2017; Franklin Schrans et al., 2018; Franklin Schrans et al., 2019; Michael J. Coblenz et al., 2019; Michael J. Coblenz et al., 2019; Reed Oei et al., 2020; Sam Blackshear et al., 2019] have been proposed that rely on advanced type systems such as session types, type states, and linear types. The global model has not been explored for dApp programming. This is unfortunate given the potential to get by with a standard typing discipline and to avoid intricacies and potential mismatches of a two-language stack. Our work fills this gap by proposing Prisma - the first language that features a global programming model for Ethereum dApps. While we focus on the Ethereum blockchain, we believe our techniques to be applicable to other smart contract platforms. Prisma enables interleaving contract and client logic within the same program and adopts a direct style (DS) notation for encoding send-and-receive operations (with our awaitCl language construct) akin to languages with async/await [Gavin M. Bierman et al., 2012; Scala async rfc]. DS addresses shortcomings with the currently dominant encoding of the protocol’s finite state machines (FSM) [Mix, 2019; Michael J. Coblenz, 2017; Franklin Schrans et al., 2018; Franklin Schrans et al., 2019; Michael J. Coblenz et al., 2019; Michael J. Coblenz et al., 2019]. We argue writing FSM style corresponds to a control-flow graph of basic blocks, which is low-level and more suited to be written by a compiler than by a human. With FSM style, the contract is a passive entity whose execution is driven by clients. whereas the DS encoding allows the contract to actively ask clients for input, fitting dApp execution where a dominant contract controls execution and diverts control to other parties when their input is needed. In the following Prisma snippet, the payout function is a function invoked by the contract when it is time to pay money to a client. In Prisma, variables, methods and classes are separated into two namespaces, one for the contract and one for the clients. The payout method is located on the contract via the annotation @co. The body of the method diverts the control to the client using awaitCl(...) { ... }, hence the contained readLine call is executed on the client. Note that no explicit send/receive operations are needed but the communication protocol is expressed through the program control flow. Only after the check client == toBePayed that the correct client replied, the current contact balance balance() is transferred to the client via transfer. @co def payout(toBePayed: Arr[Address]): Unit = { awaitCl(client => client == toBePayed) { readLine("Press enter for payout") } toBePayed.transfer(balance()) } Overall, Prisma relieves the developer from the responsibility of correctly managing distributed, asynchronous program flows and the heterogeneous technology stack. Instead, the burden is put on the compiler, which distributes the program flow by means of selective continuation-passing-style (CPS) translation and defunctionalisation and inserts guards against malicious client interactions. We needed to develop a CPS translation for the code that runs on the Ethereum Virtual Machine (EVM) since the EVM has no built-in support for concurrency primitives which could be used for asynchronous communication. While CPS translations are well-known, we cannot use them out-of-the-box because the control flow is interwoven with distribution in our case. A CPS translation that does not take distribution into account would allow malicious clients to force the contract to deviate from the intended control flow by sending a spoofed continuation. Thus, it was imperative to prove correctness of our distributed CPS translation to ensure control-flow integrity of the contract.
Phuc Nguyen Trong, Hong Khanh Vo, Huong Hoang Luong, Khiem Huynh Gia · 13 authors
YouTube connects people with each other through an online video sharing service platform. With the great devel-opment of the entertainment industry, content on YouTube is accessible to many people of different ages. However, verifying the content posted on YouTube is clean or not is a difficult problem. Dirty content is violent, pornographic and vulgar content that causes serious psychological harm to the segment of users under the age of 18, i.e., especially those of an age who are not yet aware of the harmful effects of content. Toxic will bring to the child’s behavior. Agree that Google (i.e., YouTube) has developed a YouTube Kid application where the videos are only for children under the age of 13. However, cultural and educational differences between regions strongly influence the choice of children. Select content for children. Therefore, the content restrictions on the YouTube Kid application have not yet met all the requirements of parents around the world. There have been many development directions to identify videos containing malicious content based on deep learning. However, there is no method to build a tool to support parents of children to share and identify videos with objectionable content (e.g., violence, pornography, obscene words) on the YouTube platform. In this research paper, we introduce YVC, a YouTube-verified content platform by applying blockchain’s distributed, public validation. This tool helps parents validate YouTube content and issue a report to reduce dirty content on YouTube. To demonstrate the effectiveness of our approach, we implement the proof-of-concept in the three most popular EVM platforms: Ethereum, Fantom, and the Binance smart chain. Compared to the YouTube Kids (i.e., the most common shared video platform for the under 13-year-old kid), our approach is able to capture the video preferences of the parents covering the difference areas/countries.
Using existing resources to create teaching materials can save effort and achieve the desired quality easily. Yet while some resources can be used freely for educational purposes, others such as textbooks or online course materials cannot. This is a particular problem during a pandemic when much teaching has gone online and the risk of teachers violating copyright is even higher. Therefore, a solution that facilitates the usage of copyright-restricted resources for generating teaching materials with royalty sharing is needed. Our work exploits the advantage of blockchain technology and proposes a system to bond participants with a smart contract; it securely registers records of multiple authorships and contribution distribution of a teaching material that reuses in part, existing resources. Such records can be used as authorship evidence to claim economic benefits when a material is used. We implement TMchain on Ethereum-Remix IDE with a core smart contract. To lower the cost of using blockchain, the material files are stored off-chain and tied to the word processing system for the final authorship and contribution share determination when a material is completed. Furthermore, we test TMchain with teaching material creation scenarios to demonstrate its effective and practical potential.
Isfenti Sadalia, Nisrul Irawati, Rico Nur Ilham, Abdul Nasser Hasibuan · 6 authors
This research type is quantitative version with population, particularly 5 cash of cryptocurremcies with the largest market caps in Indonesia, specifically Bitcoin, Ethereum, Ripple, Bitcoin cash, Litecoin in Indonesia. Varians data in this examine is time series facts taken from January 2017 to December 2020 by using conducting a documentation look at carried out at the ebook of monthly digital assets transaction reports, in order that the target population is 240 (four years x 12 months x five cash) monthly report information sampels. The evaluation approach of records on this take a look at makes use of mild Regression analysis (MRA) model regression and information analysis the usage of e-views statistical software. Cryptocurrency is an funding commodity which could generate returns and already has a license to be traded in trade trading through the Indonesian Commodity Futures trading Regulatory organisation. This studies is added a brand new idea of motion crypto asset that we called it pace. on this second we use velocity Token approach that adapted from the monetary Equation of change via economists known as the quantity principle of money, and its model might be large motion with the aid of token costs. in line with this approach , low speed method that crypto assets last longer within the pockets , that means that traders who to begin with attempted to invest on asset purchases speedy are actually turning to holders, or individuals who keep crypto for the long time. Many quite a variety of crypto virtual belongings traded in Indonesia through the trading corporation Indodax. The effects of records analysis within the examine show that coal price efeect has a advantageous however no longer good sized on virtual assets returns in order that it could be justified as a effective hazard evaluation model. pace of cryptocurrency does not moderate the have an impact on of coal rate on digital belongings returns.
Cryptocurrency networks that provide a new way of securing financial transactions have gained a surge of interest in recent years. However, recent studies reveal that blockchain networks are rampant with frauds and are prone to several privacy and security issues. The public availability of cryptocurrency transaction records provides an unprecedented opportunity for researchers to analyze cryptocurrency transactions. In particular, anomaly detection techniques are promising avenues for fighting illicit activities such as money laundering, terrorist financing, drug trafficking, scams, frauds, and many more.In this dissertation, we address the challenges of detecting anomalous entities on cryptocurrency networks. Firstly, we introduce effective techniques for generating features for network entities that are directly devised from raw data and highlight the utility of those features in detecting illicit accounts on the Ethereum network. Next, we enrich the proposed method by expanding the feature set through the incorporation of graph-based features that embed the relational information of networks. This also enables us to generalize our methods to instances of cryptocurrency networks with different architectural models. Based on the success of our method in anomaly detection in cryptocurrency networks, we further generalize our model to encompass a generic temporal weighted multidigraph and show the state-of-the-art results for anomaly detection in other common domains including rating and social networks. In doing so, we also investigate the challenges of employing node classification techniques for anomaly detection, which is a common practice. Here, we discuss the importance of performance metrics and evaluation settings when interpreting the efficiency of different methods and tasks, which is often overlooked by the community. Finally, we shift our focus to examining the inherent challenges of learning on dynamic networks, which is an important emerging research field with applications in drug discovery, computational finance, social networks, etc. Here, we propose solutions for providing a more robust evaluation setup for dynamic graph learning methods. The key contributions of this dissertation are twofold: First, we describe efficient techniques for detecting anomalies on cryptocurrency networks and generalize them to other real-world complex networks. Second, we focus on the temporal aspect of these networks and investigate how the dynamism of networks affects the downstream tasks and evaluation settings
Yangqun Li, Jin Qi, Lijuan Min, Hongzhi Yang · 6 authors
Web of Things (WoT) resources are not only numerous, but also have a wide range of applications and deployments. The centralized WoT resource sharing mechanism lacks flexibility and scalability, and hence cannot satisfy requirement of distributed resource sharing in large-scale environment. In response to this problem, a trusted and secure mechanism for WoT resources sharing based on context and blockchain (CWoT-Share) was proposed. Firstly, the mechanism can respond quickly to the changes of the application environment by dynamically determining resource access control rules according to the context. Then, the flexible resource charging strategies, which reduced the fees paid by the users who shared more resources and increased the fees paid by users who frequently used resources maliciously, were used to fulfill efficient sharing of WoT resources. Meanwhile, the charging strategies also achieve load balancing by dynamic selection of WoT resources. Finally, the open source blockchain platform Ethereum was used for the simulation and the simulation results show that CWoT-Share can flexibly adapt to the application environment and dynamically adjust strategies of resource access control and resource charging.