"Adversarial Learning in Real-World Fraud Detection: Challenges and ..."

Daniele Lunghi et al. (2023)

> Home

Details and statistics

DOI: 10.1145/3600046.3600051

access: closed

type: Conference or Workshop Paper

metadata version: 2023-09-24

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/de/LunghiSCB23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/de/LunghiSCB23
Daniele Lunghi, Alkis Simitsis, Olivier Caelen, Gianluca Bontempi:
Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives. DEC@SIGMOD 2023: 27-33

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.