ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2405.12295
  4. Cited By
Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks

Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks

20 May 2024
Marcin Podhajski
Jan Dubiñski
Franziska Boenisch
Adam Dziedzic
Agnieszka Pregowska
Tomasz Michalak
ArXivPDFHTML

Papers citing "Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks"

3 / 3 papers shown
Title
On the Difficulty of Defending Self-Supervised Learning against Model
  Extraction
On the Difficulty of Defending Self-Supervised Learning against Model Extraction
Adam Dziedzic
Nikita Dhawan
Muhammad Ahmad Kaleem
Jonas Guan
Nicolas Papernot
MIACV
46
22
0
16 May 2022
Increasing the Cost of Model Extraction with Calibrated Proof of Work
Increasing the Cost of Model Extraction with Calibrated Proof of Work
Adam Dziedzic
Muhammad Ahmad Kaleem
Y. Lu
Nicolas Papernot
FedML
MIACV
AAML
MLAU
55
27
0
23 Jan 2022
Stealing Links from Graph Neural Networks
Stealing Links from Graph Neural Networks
Xinlei He
Jinyuan Jia
Michael Backes
Neil Zhenqiang Gong
Yang Zhang
AAML
53
164
0
05 May 2020
1