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Ethereum smart contracts are public, immutable and distributed and, as such, they are prone to vulnerabilities sourcing from programming mistakes of developers. This paper presents SAFEVM, a verification tool for Ethereum smart contracts…
Block-STM is a parallel execution engine for smart contracts, built around the principles of Software Transactional Memory. Transactions are grouped in blocks, and every execution of the block must yield the same deterministic outcome.…
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…
The rise of AI agents powered by Large Language Models (LLMs) presents critical challenges: how to securely execute and migrate these agents across heterogeneous environments while protecting sensitive user data, maintaining availability…
This paper proposes an efficient framework to execute Smart Contract Transactions (SCTs) concurrently based on object semantics, using optimistic Single-Version Object-based Software Transactional Memory Systems (SVOSTMs) and Multi-Version…
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…
Ethereum Virtual Machine (EVM) is the run-time environment for smart contracts and its vulnerabilities may lead to serious problems to the Ethereum ecology. With lots of techniques being developed for the validation of smart contracts, the…
WebAssemly is an emerging runtime for Web applications and has been supported in almost all browsers. Recently, WebAssembly is further regarded to be a the next-generation environment for blockchain applications, and has been adopted by…
In the blockchain-based, distributed computing platform Ethereum, programs called smart contracts are compiled to bytecode and executed on the Ethereum Virtual Machine (EVM). Executing EVM bytecode is subject to monetary fees---a clear…
This paper presents MPC-EVM, the first blockchain prototype that extends the EVM to enable asynchronous MPC invocations by smart contracts during transaction executions without compromising consistency or throughput. MPC-EVM uses an…
The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application portability. Among the existing deep…
Smart contracts manage a large number of digital assets nowadays. Bugs in these contracts have led to significant financial loss. Verifying the correctness of smart contracts is, therefore, an important task. This paper presents an…
Blockchain technology is a distributed, decentralized, and immutable ledger system. It is the platform of choice for managing smart contract transactions (SCTs). Smart contracts are self-executing codes of agreement between interested…
The cryptocurrency Ethereum is the most widely used execution platform for smart contracts. Smart contracts are distributed applications, which govern financial assets and, hence, can implement advanced financial instruments, such as…
Conthereum is a concurrent Ethereum solution for intra-block parallel transaction execution, enabling validators to utilize multi-core infrastructure and transform the sequential execution model of Ethereum into a parallel one. This shift…
This paper presents EDSC, a novel smart contract platform design based on the event-driven execution model as opposed to the traditionally employed transaction-driven execution model. We reason that such a design is a better fit for many…
This paper introduces the Precision-Timed Virtual Machine (PretVM), an intermediate platform facilitating the execution of quasi-static schedules compiled from a subset of programs written in the Lingua Franca (LF) coordination language.…
We introduce the Deep Learning Vulnerability Analyzer (DLVA) for Ethereum smart contracts based on neural networks. We train DLVA to judge bytecode even though the supervising oracle can only judge source. DLVA's training algorithm is…
Smart contracts are a key component of the Web 3.0 ecosystem, widely applied in blockchain services and decentralized applications. However, the automated execution feature of smart contracts makes them vulnerable to potential attacks due…
The scaling of large language models (LLMs) is currently bottlenecked by the rigidity of distributed programming. While high-performance libraries like CuBLAS and NCCL provide optimized primitives, they lack the flexibility required for…