Related papers: Combining Graph Neural Networks with Expert Knowle…
Smart contracts are small programs that run autonomously on the blockchain, using it as their persistent memory. The predominant platform for smart contracts is the Ethereum VM (EVM). In EVM smart contracts, a problem with significant…
Smart contracts are Turing-complete programs running on the blockchain. They are immutable and cannot be modified, even when bugs are detected. Therefore, ensuring smart contracts are bug-free and well-designed before deploying them to the…
Graph data, such as chemical networks and social networks, may be deemed confidential/private because the data owner often spends lots of resources collecting the data or the data contains sensitive information, e.g., social relationships.…
Vulnerability detection is crucial for ensuring the security and reliability of software systems. Recently, Graph Neural Networks (GNNs) have emerged as a prominent code embedding approach for vulnerability detection, owing to their ability…
Understanding and characterizing the vulnerability of urban infrastructures, which refers to the engineering facilities essential for the regular running of cities and that exist naturally in the form of networks, is of great value to us.…
Smart contracts are increasingly being used to manage large numbers of high-value cryptocurrency accounts. There is a strong demand for automated, efficient, and comprehensive methods to detect security vulnerabilities in a given contract.…
Smart contracts are executable programs that enable the building of a programmable trust mechanism between multiple entities without the need of a trusted third-party. Researchers have developed several security scanners in the past couple…
Blockchain smart contracts have emerged as a transformative force in the digital realm, spawning a diverse range of compelling applications. Since solidity smart contracts across various domains manage trillions of dollars in virtual coins,…
Graph neural networks (GNNs) have attracted increasing attention due to their superior performance in deep learning on graph-structured data. GNNs have succeeded across various domains such as social networks, chemistry, and electronic…
Recent attacks exploiting errors in smart contract code had devastating consequences thereby questioning the benefits of this technology. It is currently highly challenging to fix errors and deploy a patched contract in time. Instant…
Smart contracts are programs running on a blockchain. They are immutable to change, and hence can not be patched for bugs once deployed. Thus it is critical to ensure they are bug-free and well-designed before deployment. A Contract defect…
Detecting fraudulent transactions is an essential component to control risk in e-commerce marketplaces. Apart from rule-based and machine learning filters that are already deployed in production, we want to enable efficient real-time…
This study proposes a credit card fraud detection method based on Heterogeneous Graph Neural Network (HGNN) to address fraud in complex transaction networks. Unlike traditional machine learning methods that rely solely on numerical features…
Automated vulnerability detection in critical-infrastructure software confronts a fundamental barrier: industrial software is routinely deployed as stripped, symbol-free binaries that deprive conventional Software Composition Analysis of…
Logical flaws in smart contracts are often exploited, leading to significant financial losses. Our tool, HighGuard, detects transactions that violate business logic specifications of smart contracts. HighGuard employs dynamic condition…
Smart contracts are immutable, verifiable, and autonomous pieces of code that can be deployed and ran on blockchain networks like Ethereum. Due to the immutability nature of blockchain, no change is possible on a deployed smart contract or…
Smart contracts are programs that execute inside blockchains such as Ethereum to manipulate digital assets. Since bugs in smart contracts may lead to substantial financial losses, there is considerable interest in formally proving their…
In e-commerce industry, graph neural network methods are the new trends for transaction risk modeling.The power of graph algorithms lie in the capability to catch transaction linking network information, which is very hard to be captured by…
In recent years we have witnessed a dramatic increase in the adoption and application of smart contracts in a variety of contexts such as decentralized finance, supply chain management, and identity management. However, a critical stumbling…
One of the most significant challenges in the field of software code auditing is the presence of vulnerabilities in software source code. Every year, more and more software flaws are discovered, either internally in proprietary code or…