Titlebook: Blockchain and Trustworthy Systems; 5th International Co Jiachi Chen,Bin Wen,Ting Chen Conference proceedings 2024 The Editor(s) (if applic

Spartan

Occlusion

https://doi.org/10.1007/978-3-540-79862-0sers’ search intentions, behavior, and interests from access patterns, which can be used for targeted attacks, phishing, or identity theft. Access pattern disclosure may also jeopardize the confidentiality of the searched data, as it may reveal sensitive information related to the queried data..Trad

tangle

Willy Schneider,Alexander Hennigfor consortium blockchain faces serious challenges: Firstly, due to the sealied feature of consortium blockchain, it should build up the effective and robust computation mechanism for distributed supervision between various platforms; Secondly, due to the sensitivity of supervision data, data transm

誰在削木頭

Willy Schneider,Alexander Hennign security management. Because of this, the application of a blockchain-based collaborative healthcare system has been born, and blockchain has become the main driving force for the development of collaborative healthcare. However, the existing blockchain HIS (Hospital Management Information System)

Encumber

A General Smart Contract Vulnerability Detection Framework with?Self-attention Graph Poolingous common vulnerabilities via a uniform framework. We leveraged the Abstract Syntax Trees (AST) and self-attention-based graph pooling models to generate topological graphs from smart contract code analysis. We adopted Graph Neural Networks for vulnerability detection. Experimental results demonstr

胰臟

后退

MF-Net: Encrypted Malicious Traffic Detection Based on?Multi-flow Temporal Features, we use a public dataset provided by Qi An Xin for experimental evaluation. Experimental results show that MF-Net outperforms Graph Neural Network based multi-flow method. MF-Net can achieve 98.13% accuracy and 98.10% F1 score using 5 flows, which enables effective encrypted malicious traffic detec

forebear

ePoW Energy-Efficient Blockchain Consensus Algorithm for?Decentralize Federated Learning System in?Rment metrics to facilitate the selection of participating nodes in the ePoW competition. Following a successful BFL global generation event, the dynamic difficulty adjustment mechanism collaborates with the engagement metrics to identify the most reliable node and mitigate resource consumption durin

Obvious

Magnitude