English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Blockchain technology has the characteristics of decentralization,traceability and tamper proof, which creates a reliable decentralizedtransaction mode, further accelerating the development of the blockchainplatforms. However, with the popularization of various financial applications,security problems caused by blockchain digital assets, such as moneylaundering, illegal fundraising and phishing fraud, are constantly on the rise.Therefore, financial security has become an important issue in the blockchainecosystem, and identifying the types of accounts in blockchain (e.g. miners,phishing accounts, Ponzi contracts, etc.) is of great significance in riskassessment and market supervision. In this paper, we construct an accountinteraction graph using raw blockchain data in a graph perspective, andproposes a joint learning framework for account identity inference onblockchain with graph contrast. We first capture transaction feature andcorrelation feature from interaction graph, and then perform sampling and dataaugmentation to generate multiple views for account subgraphs, finally jointlytrain the subgraph contrast and account classification task. Extensiveexperiments on Ethereum datasets show that our method achieves significantadvantages in account identity inference task in terms of classificationperformance, scalability and generalization.

BlockGC: A Joint Learning Framework for Account Identity Inference on Blockchain with Graph Contrast