In recent years, phishing scams have become the crime type with the largest money involved on Ethereum, the second-largest blockchain platform. Meanwhile, graph neural network (GNN) has shown promising performance in various node classification tasks. However, for Ethereum transaction data, which could be naturally abstracted to a real-world complex graph, the scarcity of labels and the huge volume of transaction data make it difficult to take advantage of GNN methods. Here in this paper, to address the two challenges, we propose a Self-supervised Incremental deep Graph learning model (SIEGE), for the phishing scam detection problem on Ethereum. In our model, two pretext tasks designed from spatial and temporal perspectives help us effectively learn useful node embedding from the huge amount of unlabelled transaction data. And the incremental paradigm allows us to efficiently handle large-scale transaction data and help the model maintain good performance when the data distribution is drastically changing. We collect transaction records about half a year from Ethereum and our extensive experiments show that our model consistently outperforms strong baselines in both transductive and inductive settings.
Jun 18, 2021·2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC)2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC)
Ethereum is a permissionless blockchain with a Turing complete machine for smart contracts. Ethereum's Gas mechanism, which charges the execution of each operation code, is proposed to ensure the termination of smart contracts that run in the EVM (Ethereum Virtual Machine) and to compensate the computational usage. Thus, the Gas awarded should be rational to the required computational, to ensure the alignment and to avoid the denial of services attack. Currently, in Ethereum, Gas awarded is set statically for each operational code in the smart contract, but it is unknown if whether these values are correct or not for various computer architectures. Therefore, in this paper, we show the most common used operational codes and the rationality of the Gas to the CPU usage for a selected set of the EVM's operational codes.
Sharding is a popular way to achieve scalability in blockchain protocols, increasing their throughput by partitioning the set of transaction validators into a number of smaller committees, splitting the workload. Existing approaches for blockchain sharding, however, do not scale well when concurrent transactions alter the same replicated state component—a common scenario in Ethereum-style smart contracts.
Since the emergence of Ethereum, blockchain-based decentralized applications (DApps) have become increasingly popular and important. To balance the security, performance, and costs, a DApp typically consists of two layers: an on-chain layer to execute transactions and store crucial data on the blockchain and an off-chain layer to interact with users. A DApp needs to synchronize its off-chain layer with the on-chain layer proactively. Otherwise, the inconsistent data in the off-chain layer could mislead users and cause undesirable consequences, e.g., loss of transaction fees. However, transactions sent to the blockchain are not guaranteed to be executed and could even be reversed after execution due to chain reorganization. Such non-determinism in the transaction execution is unique to blockchain. DApp developers may fail to perform the on-chain-off-chain synchronization accurately due to their lack of familiarity with the complex transaction lifecycle. In this work, we investigate the challenges of synchronizing on-chain and off-chain data in Ethereum-based DApps. We present two types of bugs that could result in inconsistencies between the on-chain and off-chain layers. To help detect such on-chain-off-chain synchronization bugs, we introduce a state transition model to guide the testing of DApps and propose two effective oracles to facilitate the automatic identification of bugs. We build the first testing framework, DArcher, to detect on-chain-off-chain synchronization bugs in DApps. We have evaluated DArcher on 11 popular real-world DApps. DArcher achieves high precision (99.3%), recall (87.6%), and accuracy (89.4%) in bug detection and significantly outperforms the baseline methods. It has found 15 real bugs in the 11 DApps. So far, six of the 15 bugs have been confirmed by the developers, and three have been fixed. These promising results demonstrate the usefulness of DArcher.
Smart grid (SG) systems necessitate secure demand response management (DRM) schemes for real-time decisions making to increase the effectiveness and stability of SG systems along with data security. Motivated from the aforementioned discussion, in this article, we propose Q-SDRM, a secure DRM scheme for home energy management (HEM) using reinforcement learning (RL) and ethereum blockchain (EBC) to facilitate energy consumption reduction and decrease energy costs. In cooperation with RL,$Q$-learning is adopted to make optimal price decisions using Markov decision process (MDP) to reduce energy consumption, which benefits both consumers and utility providers. Then, Q-SDRM uses ethereum smart-contract (ESC) to deal with data security issues and incorporate with off-chain storage interplanetary file system (IPFS) that handles data storage costs issue. Experimental results reveal the effectiveness of the proposed Q-SDRM scheme, which significantly reduces energy consumption and energy cost. The proposed scheme also provides secure access to energy data in real time compared with state-of-the-art approaches regarding different evaluation metrics, such as scalability, overall energy cost, and data storage cost.
Smart contracts hold digital coins worth billions of dollars, their security issues have drawn extensive attention in the past years. Towards smart contract vulnerability detection, conventional methods heavily rely on fixed expert rules, leading to low accuracy and poor scalability. Recent deep learning approaches alleviate this issue but fail to encode useful expert knowledge. In this paper, we explore combining deep learning with expert patterns in an explainable fashion. Specifically, we develop automatic tools to extract expert patterns from the source code. We then cast the code into a semantic graph to extract deep graph features. Thereafter, the global graph feature and local expert patterns are fused to cooperate and approach the final prediction, while yielding their interpretable weights. Experiments are conducted on all available smart contracts with source code in two platforms, Ethereum and VNT Chain. Empirically, our system significantly outperforms state-of-the-art methods. Our code is released.
This paper presents iBatch, a middleware system running on top of an operational Ethereum network to enable secure batching of smart-contract invocations against an untrusted relay server off-chain. iBatch does so at a low overhead by validating the server's batched invocations in smart contracts without additional states. The iBatch mechanism supports a variety of policies, ranging from conservative to aggressive batching, and can be configured adaptively to the current workloads. iBatch automatically rewrites smart contracts to integrate with legacy applications and support large-scale deployment. For cost evaluation, we develop a platform with fast and cost-accurate transaction replaying, build real transaction benchmarks on popular Ethereum applications, and build a functional prototype of iBatch on Ethereum. The evaluation results show that iBatch saves 14.6%-59.1% Gas cost per invocation with a moderate 2-minute delay and 19.06%-31.52% Ether cost per invocation with a delay of 0.26-1.66 blocks.
Over the past few years, there has been an alarming rise in the cyber attacks which are being carried out by Social Engineering Technique. Email is widely used for communication purposes and thus Spam Email Attacks are found to be the most common social engineering technique used by attackers to intrude into the system and perform malicious operations. Almost 85% of the overall email traffic is found to be spam (122.3 billion spam e-mails transmitted per day), which causes severe damage like, data loss, account compromise, ransomware attack, malware infection into the organization/personal systems. Various Artificial Intelligence-based methods (based on reviewing the content of an email) are created to identify spam emails, still, the count of hacks and loss due to spam emails is increasing on daily basis. On the other hand, blockchain being one of the cutting edges and disruptive technology has gained attention in the past few years. In this literature, authors have proposed a blockchain-based system to counter, prevent and identify spam emails. Authors have integrated the wallet-to-wallet transaction in Ethereum, with an existing email system to identify spam and legitimate email. The proposed framework is not based on verifying the content of an email at mailing servers instead the server verifies or check if or not the Cryptocurrency is paid, and thus the proposed framework is supposed to have small workloads and better performance throughput in terms of sending and receiving emails. The authors were able to create a Proof of Concept of the proposed methodology. All the endpoints created to achieve the same were executed in less than 1.5 sec of Elapse Time Average. The proposed framework will act as a Single Source of truth in identifying the Spam E-Mail.
Flavio Corradini, Alessandro Marcelletti, Andrea Morichetta, Andrea Polini · 7 authors
As a disruptive technology, the blockchain is continuously finding novel application contexts, bringing new opportunities and radical changes. In this paper, we use blockchain as a communication infrastructure to support multi-party business processes. In particular, through smart contracts specifically generated by the mentioned business process, it is possible to derive a trustable infrastructure enabling the interaction among parties. Moreover, the emergence of different blockchain technologies, satisfying different characteristics, gives the possibility to support the same business process dealing with different non-functional needs. In this paper, we propose a novel engineering methodology supported by a practical framework called Multi-Chain. It permits to derive, using a model-driven strategy, a blockchain-based infrastructure, that can be deployed over a specific blockchain technology (e.g., Ethereum or Hyperledger Fabric). The objective is to permit the single definition and multiple deployments of the business process, to deliver the same functionalities, but satisfying different non-functional needs. In such a way, organisations willing to cooperate can select the multi-party business process and the blockchain technology they would like to use to satisfy their needs. Using Multi-Chain, they will be able to automatically derive from a Business Process Modelling Notation (BPMN) choreography diagram a blockchain infrastructure ready to be used. This overcomes the need to get acquainted with many details of the specific technology.
Abstract In today's scenario, many news related to counterfeit land titles, fraud land registry, delay in ownership transfer, the involvement of government officers in fraudulent activities is frequently being heard. However, this depicts that the existing land registry system is not efficient to provide security and timely settlement of transactions between the seller and buyer. To solve this problem, we proposed a blockchain‐based land registry system in this article. The specialty and popularity of blockchain technology is its transparency and security. Blockchain is being inculcated with the trait of persistence, immutability, decentralization. Its ascent to new opportunity of efficiency and cost saving. It can provide right framing for digital asset, online payment, and transfer of remittance. Additional to this it can check upon black money laundering. Enterprise that can use blockchain technology can gain faith of consumer. In this article, we proposed a decentralized application. In particular, for creating and deploying the smart contract, we used Ethereum network. The deployed contracts are interacted through frontend web pages. React is used for the development of web page. For server and routing purposes, Next.js is used. Finally, the results and analysis show that our proposed model is efficient and viable.
Blockchain-based smart contract platforms have traditionally employed the transaction-driven execution model. This paper presents an alternate framework for blockchain-based smart contract execution called EDSC. Our platform design presents a novel approach to tackle the scalability and performance challenges facing the smart contract ecosystem. We base EDSC's design on the Ethereum template, and it can be readily implemented for other existing smart contract platforms. To evaluate our design, we perform an experimental implementation using the Ethereum client. Our experiments with performance modeling show, on average, a 2.2 to 4.6 times reduced total latency of event-triggered smart contracts, demonstrating the effectiveness of the design in supporting time-sensitive applications. Additionally, we comment on the design's potential security aspects and demonstrate its utility by discussing potential use cases.
BACKGROUND: Health care systems are currently undergoing a digital transformation that has been primarily triggered by emerging technologies, such as artificial intelligence, the Internet of Things, 5G, blockchain, and the digital representation of patients using (mobile) sensor devices. One of the results of this transformation is the gradual virtualization of care. Irrespective of the care environment, trust between caregivers and patients is essential for achieving favorable health outcomes. Given the many breaches of information security and patient safety, today's health information system portfolios do not suffice as infrastructure for establishing and maintaining trust in virtual care environments. OBJECTIVE: This study aims to establish a theoretical foundation for a complex health care system intervention that aims to exploit a cryptographically secured infrastructure for establishing and maintaining trust in virtualized care environments and, based on this theoretical foundation, present a proof of concept that fulfills the necessary requirements. METHODS: This work applies the following framework for the design and evaluation of complex intervention research within health care: a review of the literature and expert consultation for technology forecasting. A proof of concept was developed by following the principles of design science and requirements engineering. RESULTS: This study determined and defined the crucial functional and nonfunctional requirements and principles for enhancing trust between caregivers and patients within a virtualized health care environment. The cornerstone of our architecture is an approach that uses blockchain technology. The proposed decentralized system offers an innovative governance structure for a novel trust model. The presented theoretical design principles are supported by a concrete implementation of an Ethereum-based platform called VerifyMed. CONCLUSIONS: A service for enhancing trust in a virtualized health care environment that is built on a public blockchain has a high fit for purpose in Healthcare 4.0.
Abdullah Lakhan, Mazin Abed Mohammed, Ahmed Noori Rashid, Seifedine Kadry · 7 authors
The Internet of Medical Things (IoMT) is increasingly being used for healthcare purposes. IoMT enables many sensors to collect patient data from various locations and send it to a distributed hospital for further study. IoMT provides patients with a variety of paid programmes to help them keep track of their health problems. However, the current system services are expensive, and offloaded data in the healthcare network are insecure. The research develops a new, cost-effective and stable IoMT framework based on a blockchain-enabled fog cloud. The study aims to reduce the cost of healthcare application services as they are processing in the system. The study devises an IoMT system based on different algorithm techniques, such as Blockchain-Enable Smart-Contract Cost-Efficient Scheduling Algorithm Framework (BECSAF) schemes. Smart-Contract Blockchain schemes ensure data consistency and validation with symmetric cryptography. However, due to the different workflow tasks scheduled on other nodes, the heterogeneous, earliest finish, time-based scheduling deals with execution under their deadlines. Simulation results show that the proposed algorithm schemes outperform all existing baseline approaches in terms of the implementation of applications.
Alexandre Augusto Giron, Jean Everson Martina, Ricardo Felipe Custódio
Steganography is one of the ways to hide data between parties. Its use can be worrisome, e.g., to hide illegal communications. Researchers found that public blockchains can be an attractive place to hide communications; however, there is not much evidence of actual use in blockchains. Besides, previous work showed a lack of steganalysis methods for blockchains. In this context, we present a steganalysis approach for blockchains, evaluating it in Bitcoin and Ethereum, both popular cryptocurrencies. The main objective is to answer if one can find steganography in real case scenarios, focusing on LSB of addresses and nonces. Our sequential analysis included 253 GiB and 107 GiB of bitcoin and ethereum, respectively. We also analyzed up to 98 million bitcoin clusters. We found that bitcoin clusters could carry up to 360 KiB of hidden data if used for such a purpose. We have not found any concrete evidence of hidden data in the blockchains. The sequential analysis may not capture the perspective of the users of the blockchain network. In this case, we recommend clustering analysis, but it depends on the clustering method's accuracy. Steganalysis is an essential aspect of blockchain security.
Open access
Advanced Steganography and Watermarking Techniques
This article is devoted to the analysis of the legal framework for the digitization of public procurement, doctrinal approaches to the use of smart contracts in procurement. It studies the process and technologies of formation and development of smart contracts, blockchain, contracting in ethereum, the mechanisms of using smart contracts in public procurement. It also explores aspects that need to be addressed in improving the procurement system through smart contracts and develops recommendations.
Physical documents have many challenges, due to being difficult to exchange and the potential of being lost and sabotaged. Digital documents seem to address some of these challenges, but because of the use of the Internet and reliance on third parties to share and preserve such documents, the privacy and integrity of the digital documents became difficult to maintain. The blockchain technology that Satoshi Nakamoto has proposed for financial transactions can be used to solve the problems of trust in centralized systems and the subversion and alteration thatthese transactions may be exposed to. Blockchain-based systems have shown their effectiveness and ability to solve most security problems related to exchanging systems' transactions. Hence,A decentralized system for exchanging digital documents, using Ethereum blockchain and InterPlanetary File System (IPFS), has been proposed to overcome the problems of using trusted third-parties in exchanging digital documents. The proposed system provides immutable and irreversible logs of the process of sending and receiving documents. In this framework, all registered users can encrypt the documents using the Advanced Encryption Standard (AES) Algorithm, send, and receive documents using the Ethereum Blockchain's smart contract. The framework was simulated locally using Ganache Blockchain and tested on the official Ethereum test network Ropsten, and the experimental results showed the feasibility of the proposed scheme. The smart contract used in the Ethereum blockchain was written in the Solidity programming language, and the website that was needed to interact with the blockchain was built using React and other different javascript libraries like web3. Additionally, Metamask wallet was used to create the Ethereum accounts which are required to connect and communicate with the Smart Contract that is implemented in the Ethereum blockchain. Finally, the model's results indicated that the model may cost an average of 0.0552$ per transaction, and this shows that the system is affordable. Also, the model has satisfied the three main security requirements which are confidentiality, integrity, and availability by using the suitable countermeasure for each one of them.
Jonas Schiffl, Matthias Grundmann, Marc Leinweber, Oliver Stengele · 6 authors
Ethereum is a platform for deploying smart contracts, which due to their public nature and the financial value of the assets they manage are attractive targets for attacks. With asset management as a main task of smart contracts, access control aspects are naturally part of the application itself, but also of the functions implemented in a smart contract. Therefore, it is desirable to establish the correctness of smart contracts and their access control on application and single-function level through formal methods. However, there is no established methodology of formalising and verifying correctness properties of smart contracts. In this work, we make an attempt in this direction on the basis of a case study. We choose an existing smart contract application which aims to ascertain the integrity of binary files distributed over the Internet by means of decentralised identity management and access control. We formally specify and verify correctness at the level of single functions as well as temporal properties of the overall application. We demonstrate how to use verified low-level correctness properties for showing correctness at the higher level. In addition, we report on our experience with existing verification tools.
Kaihua Qin, Liyi Zhou, Pablo Gamito, Philipp Jovanovic · 5 authors
Financial speculators often seek to increase their potential gains with leverage. Debt is a popular form of leverage, and with over 39.88B USD of total value locked (TVL), the Decentralized Finance (DeFi) lending markets are thriving. Debts, however, entail the risks of liquidation, the process of selling the debt collateral at a discount to liquidators. Nevertheless, few quantitative insights are known about the existing liquidation mechanisms. In this paper, to the best of our knowledge, we are the first to study the breadth of the borrowing and lending markets of the Ethereum DeFi ecosystem. We focus on Aave, Compound, MakerDAO, and dYdX, which collectively represent over 85% of the lending market on Ethereum. Given extensive liquidation data measurements and insights, we systematize the prevalent liquidation mechanisms and are the first to provide a methodology to compare them objectively. We find that the existing liquidation designs well incentivize liquidators but sell excessive amounts of discounted collateral at the borrowers' expenses. We measure various risks that liquidation participants are exposed to and quantify the instabilities of existing lending protocols. Moreover, we propose an optimal strategy that allows liquidators to increase their liquidation profit, which may aggravate the loss of borrowers.
Blockchain is a tamper-proof distributed ledger for tracking public or private pair transactions in pair networks that can not be retroactively changed without modifying all corresponding network blocks. The Consensus Protocol upgrades a blockchain, which guarantees a sequential, unambiguous transaction ordering. Blocks ensure that the blockchain is integral and uniform across a network of distributed nodes. Different blockchain implementations use different consensus protocols. This paper offers a brief overview of the most important discrepancies between the Hyperledger Fabric and Ethereum distributed ledger technologies (DLT).
Blockchain technology can be used in the food sector to improve food quality, product recalls, inventory tracking, demand response, traceability, transparency, consumer trust, and mitigating recall costs. Growing interest in Blockchain food traceability technology i.e., to track any food, feed, food-producing animals, or substances used for consumption through all stages of production, processing, and distribution necessitates a systematic literature review. The objective of this systematic literature review (SLR) was to identify the advantages of using Blockchain in food supply chains through studies on Blockchain implementation for food traceability. This study investigated 14 primary recent studies published between 2017 and 2020 from web sources and digital libraries. According to the findings, 21% of papers were published in 2017 and 43% in 2020, indicating that the use of Blockchain technology in food traceability is gaining traction over time. The 14 Blockchain systems studied in this SLR used four different Blockchain platforms: 8 out 14 used Ethereum. Blockchain-based traceability systems provided numerous traceability features, such as complete farm-to-fork traceability, recoding of every single transaction, digital tracking, decentralised file systems, visualisation methods for intuitively displaying risks, and the ability to reconstruct the product's history up to the origin for the purpose of quality verification.
COVID-19 has made eHealth an imperative. The pandemic has been a true catalyst for remote eHealth solutions such as teleHealth. Telehealth facilitates care, diagnoses, and treatment remotely, making them more efficient, accessible, and economical. However, they have a centralized identity management system that restricts the interoperability of patient and healthcare provider identification. Thus, creating silos of users that are unable to authenticate themselves beyond their eHealth application's domain. Furthermore, the consumers of remote eHealth applications are forced to trust their service providers completely. They cannot check whether their eHealth service providers adhere to the regulations to ensure the security and privacy of their identity information. Therefore, we present a blockchain-based decentralized identity management system that allows patients and healthcare providers to identify and authenticate themselves transparently and securely across different eHealth domains. Patients and healthcare providers are uniquely identified by their health identifiers (healthIDs). The identity attributes are attested by a healthcare regulator, indexed on the blockchain, and stored by the identity owner. We implemented smart contracts on an Ethereum consortium blockchain to facilities identification and authentication procedures. We further analyze the performance using different metrics, including transaction gas cost, transaction per second, number of blocks lost, and block propagation time. Parameters including block-time, gas-limit, and sealers are adjusted to achieve the optimal performance of our consortium blockchain.