GOLDRUSH: Rule Sharing System for Fraud Detection

Summary: GOLDRUSH enables cross-context sharing and adaptation of fraud-detection rules. It semantically abstracts rule conditions for new contexts and uses cost-benefit guided algorithms to identify effective adaptations, demonstrated on a real fraud event. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 11694
Venue: VLDB
Year: 2018
Pagerank: 4.4039656e-05
Overall Rank: 9,055 | 37.01%
DOI: 10.14778/3229863.3236244

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
11,266	MINT: Detecting Fraudulent Behaviors from Time-series Relational Data	2023	VLDB	4.1945683e-05
11,595	Minimization of Classifier Construction Cost for Search Queries	2020	SIGMOD	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank

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