Related papers: Graph Neural Networks Enhanced Smart Contract Vuln…
For data privacy, system reliability, and security, Blockchain technologies have become more popular in recent years. Despite its usefulness, the blockchain is vulnerable to cyber assaults; for example, in January 2019 a 51% attack on…
Graph neural networks (GNNs) have excelled in various graph learning tasks, particularly node classification. However, their performance is often hampered by noisy measurements in real-world graphs, which can corrupt critical patterns in…
The rapid adoption of blockchain technology highlighted the importance of ensuring the security of smart contracts due to their critical role in automated business logic execution on blockchain platforms. This paper provides an empirical…
The blockchain constitutes a technology-based, rather than social or regulation based, means to lower uncertainty about one another in order to exchange value. However, its use may very well also lead to increased complexity resulting from…
Ethereum is the largest blockchain platform that supports smart contracts. Users deploy smart contracts by publishing the smart contract's bytecode to the blockchain. Since the data in the blockchain cannot be modified, even if these…
The digital revolution has significantly impacted financial transactions, leading to a notable increase in credit card usage. However, this convenience comes with a trade-off: a substantial rise in fraudulent activities. Traditional machine…
This chapter contributes to evolving the versatility and complexity of blockchain-enabled services through extending the functionality of blockchain-enforced smart contracts. The contributions include: (i) a method for automated management…
The rise of modern blockchains has facilitated the emergence of smart contracts: autonomous programs that live and run on the blockchain. Smart contracts have seen a rapid climb to prominence, with applications predicted in law, business,…
With a growing number of institutions involved in the global education market, it has become increasingly challenging to verify the authenticity of academic achievements such as CVs and diplomas. Blockchain is an enabling technology that…
Background: Health 3.0 allows decision making to be based on longitudinal data from multiple institutions, from across the patient's healthcare journey. In such a distributed setting, blockchain smart contracts can act as neutral…
Traditional approaches for smart contract analysis often rely on intermediate representations such as abstract syntax trees, control-flow graphs, or static single assignment form. However, these methods face limitations in capturing both…
Smart contracts are blockchain programs that often handle valuable assets. Writing secure smart contracts is far from trivial, and any vulnerability may lead to significant financial losses. To support developers in identifying and…
We examine blockchain technologies, especially smart contracts, as a platform for decentralized applications. By providing a basis for consensus, blockchain promises to upend business models that presuppose a central authority. However,…
Blockchains facilitate secure resource transactions through smart contracts, yet these digital agreements are prone to vulnerabilities, particularly when interacting with external contracts, leading to substantial monetary losses.…
The immutable nature of blockchain technology, while revolutionary, introduces significant security challenges, particularly in smart contracts. These security issues can lead to substantial financial losses. Current tools and approaches…
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…
Corporate fraud detection aims to automatically recognize companies that conduct wrongful activities such as fraudulent financial statements or illegal insider trading. Previous learning-based methods fail to effectively integrate rich…
In recent years, we have seen a great deal of both academic and practical interest in the topic of vulnerabilities in smart contracts, particularly those developed for the Ethereum blockchain. While most of the work has focused on detecting…
Graph Neural Networks (GNNs) have emerged as a powerful, data-driven approach for Quantum Error Correction (QEC) decoding, capable of learning complex noise characteristics directly from syndrome data. However, the robustness of these…
Graph convolutional networks (GCNs) are vulnerable to perturbations of the graph structure that are either random, or, adversarially designed. The perturbed links modify the graph neighborhoods, which critically affects the performance of…