相关论文: DogeFuzz: A Simple Yet Efficient Grey-box Fuzzer f…

The rapid growth of Ethereum has made it more important to quickly and accurately detect smart contract vulnerabilities. While machine-learning-based methods have shown some promise, many still rely on rule-based preprocessing designed by…

Patch fuzzing is a technique aimed at identifying vulnerabilities that arise from newly patched code. While researchers have made efforts to apply patch fuzzing to testing JavaScript engines with considerable success, these efforts have…

Ethereum Smart Contracts based on Blockchain Technology (BT) enables monetary transactions among peers on a blockchain network independent of a central authorizing agency. Ethereum Smart Contracts are programs that are deployed as…

Smart contracts are small programs on the blockchain that often handle valuable assets. Vulnerabilities in smart contracts can be costly, as time has shown over and over again. Countermeasures are high in demand and include best practice…

Deep learning (DL) systems can make our life much easier, and thus are gaining more and more attention from both academia and industry. Meanwhile, bugs in DL systems can be disastrous, and can even threaten human lives in safety-critical…

Internet of Things (IoT) consists of a large number of devices connected through a network, which exchange a high volume of data, thereby posing new security, privacy, and trust issues. One way to address these issues is ensuring data…

With the rapid advancement of blockchain technology, smart contracts have enabled the implementation of increasingly complex functionalities. However, ensuring the security of smart contracts remains a persistent challenge across the stages…

This paper reports on the development of a formal symbolic process virtual machine (FSPVM) denoted as FSPVM-E for verifying the reliability and security of Ethereum-based services at the source code level of smart contracts, and a Coq proof…

The rapid growth of decentralized finance (DeFi) has led to the widespread use of automated agents, or bots, within blockchain ecosystems like Ethereum, Binance Smart Chain, and Solana. While these bots enhance market efficiency and…

In this paper, we explore remarkable similarities between multi-transactional behaviors of smart contracts in cryptocurrencies such as Ethereum and classical problems of shared-memory concurrency. We examine two real-world examples from the…

Smart contracts on Ethereum handle millions of U.S. Dollars and other financial assets. In the past, attackers have exploited smart contracts to steal these assets. The Ethereum community has developed plenty of tools to detect vulnerable…

Ethereum's scalability has been a major concern due to its limited transaction throughput and high fees. To address these limitations, Polygon has emerged as a sidechain solution that facilitates asset transfers between Ethereum and…

Timing vulnerabilities in processors have emerged as a potent threat. As processors are the foundation of any computing system, identifying these flaws is imperative. Recently fuzzing techniques, traditionally used for detecting software…

Smart contracts play a pivotal role in blockchain ecosystems, and fuzzing remains an important approach to securing smart contracts. Even though mutation scheduling is a key factor influencing fuzzing effectiveness, existing fuzzers have…

Softwarization and virtualization in 5G and beyond necessitate thorough testing to ensure the security of critical infrastructure and networks, requiring the identification of vulnerabilities and unintended emergent behaviors from protocol…

Millions of smart contracts have been deployed onto the Ethereum platform, posing potential attack subjects. Therefore, analyzing contract binaries is vital since their sources are unavailable, involving identification comprising function…

Ethereum smart contracts are distributed programs running on top of the Ethereum blockchain. Since program flaws can cause significant monetary losses and can hardly be fixed due to the immutable nature of the blockchain, there is a strong…

In recent publications, we presented a novel formal symbolic process virtual machine (FSPVM) framework that combined higher-order theorem proving and symbolic execution for verifying the reliability and security of smart contracts developed…

As Ethereum continues to thrive, the Ethereum Virtual Machine (EVM) has become the cornerstone powering tens of millions of active smart contracts. Intuitively, security issues in EVMs could lead to inconsistent behaviors among smart…

Fuzzing is widely used for software vulnerability detection. There are various kinds of fuzzers with different fuzzing strategies, and most of them perform well on their targets. However, in industry practice and empirical study, the…