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Many real-world data comes in the form of graphs, such as social networks and protein structure.
Wherefore Art Thou R3579X? Anonymized Social Networks, Hidden Patterns, and Structural Steganography
Lars Backstrom, Cynthia Dwork, and Jon Kleinberg · 2007
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Visualizing Data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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Inferring Social Ties from Geographic Coincidences
David J. Crandall, Lars Backstrom, Dan Cosley, Siddharth Suri, Daniel Huttenlocher, and Jon Kleinberg · 2010
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Networks, Crowds, and Markets: Reasoning About a Highly Connected World
David Easley and Jon Kleinberg · 2010
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Friendship and Mobility: User Movement in Location-based Social Networks
Eunjoon Cho, Seth A. Myers, and Jure Leskovec · 2011
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Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing
Matt Fredrikson, Eric Lantz, Somesh Jha, Simon Lin, David Page, and Thomas Ristenpart · 2014
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Mining of Massive Datasets
Jure Leskovec, Anand Rajaraman, and Jeffrey David Ullman · 2014
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Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
Matt Fredrikson, Somesh Jha, and Thomas Ristenpart · 2015
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Stealing Machine Learning Models via Prediction APIs
Florian Tramèr, Fan Zhang, Ari Juels, Michael K. Reiter, and Thomas Ristenpart · 2016
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walk2friends: Inferring Social Links from Mobility Profiles
Michael Backes, Mathias Humbert, Jun Pang, and Yang Zhang · 2017
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Inductive Representation Learning on Large Graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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AttriInfer: Inferring User Attributes in Online Social Networks Using Markov Random Fields
Jinyuan Jia, Binghui Wang, Le Zhang, and Neil Zhenqiang Gong · 2017
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Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf and Max Welling · 2017
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Membership Inference Attacks Against Machine Learning Models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017
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Attention is All you Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski and Stephan Günnemann · 2018
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Differentially Private Data Generative Models
Qingrong Chen, Chong Xiang, Minhui Xue, Bo Li, Nikita Borisov, Dali Kaarfar, and Haojin Zhu · 2018
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Adversarial Attack on Graph Structured Data
Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, and Le Song · 2018
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Machine Learning with Membership Privacy using Adversarial Regularization
Milad Nasr, Reza Shokri, and Amir Houmansadr · 2018
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Adversarial Attack and Defense on Graph Data: A Survey
Lichao Sun, Yingtong Dou, Carl Yang, Ji Wang, Philip S. Yu, Lifang He, and Bo Li · 2018
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Graph Attention Networks
Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
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Stealing Hyperparameters in Machine Learning
Binghui Wang and Neil Zhenqiang Gong · 2018
Cited alongside, same era.
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, and Somesh Jha · 2018
Cited alongside, same era.
Adversarial Attacks on Neural Networks for Graph Data
Daniel Zügner, Amir Akbarnejad, and Stephan Günnemann · 2018
Cited alongside, same era.
Adversarial Attacks on Node Embeddings via Graph Poisoning
Extracting Training Data from Large Language Models
Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, and Colin Raffel · 2020
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GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models
Dingfan Chen, Ning Yu, Yang Zhang, and Mario Fritz · 2020
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A Survey of Adversarial Learning on Graphs
Liang Chen, Jintang Li, Jiaying Peng, Tao Xie, Zengxu Cao, Kun Xu, Xiangnan He, and Zibin Zheng · 2020
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Label-Only Membership Inference Attacks
Christopher A. Choquette Choo, Florian Tramèr, Nicholas Carlini, and Nicolas Papernot · 2020
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Aleksandar Bojchevski and Stephan Günnemann · 2019
Cited alongside, same era.
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks
Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song · 2019
Cited alongside, same era.
LOGAN: Evaluating Privacy Leakage of Generative Models Using Generative Adversarial Networks
Jamie Hayes, Luca Melis, George Danezis, and Emiliano De Cristofaro · 2019
Cited alongside, same era.
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples
Jinyuan Jia, Ahmed Salem, Michael Backes, Yang Zhang, and Neil Zhenqiang Gong · 2019
Cited alongside, same era.
Exploiting Unintended Feature Leakage in Collaborative Learning
Luca Melis, Congzheng Song, Emiliano De Cristofaro, and Vitaly Shmatikov · 2019
Cited alongside, same era.
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
Milad Nasr, Reza Shokri, and Amir Houmansadr · 2019
Cited alongside, same era.
Knockoff Nets: Stealing Functionality of Black-Box Models
Tribhuvanesh Orekondy, Bernt Schiele, and Mario Fritz · 2019
Cited alongside, same era.
Vasisht Duddu, Antoine Boutet, and Virat Shejwalkar · 2020
Later among the works it cites.
High Accuracy and High Fidelity Extraction of Neural Networks
Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, and Nicolas Papernot · 2020
Later among the works it cites.
Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study
Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, and Jiliang Tang · 2020
Later among the works it cites.
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference
Klas Leino and Matt Fredrikson · 2020
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Label-Leaks: Membership Inference Attack with Label
Zheng Li and Yang Zhang · 2020
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Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models
Benedek Rozemberczki and Rik Sarkar · 2020
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Overlearning Reveals Sensitive Attributes
Congzheng Song and Vitaly Shmatikov · 2020
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Membership Encoding for Deep Learning
Congzheng Song and Reza Shokri · 2020
Later among the works it cites.
Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization
Bang Wu, Xiangwen Yang, Shirui Pan, and Xingliang Yuan · 2020
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Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, and Anil K. Jain · 2020
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The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks
Yuheng Zhang, Ruoxi Jia, Hengzhi Pei, Wenxiao Wang, Bo Li, and Dawn Song · 2020
Later among the works it cites.
Backdoor Attacks to Graph Neural Networks
Zaixi Zhang, Jinyuan Jia, Binghui Wang, and Neil Zhenqiang Gong · 2020
Later among the works it cites.
Stealing Links from Graph Neural Networks
Xinlei He, Jinyuan Jia, Michael Backes, Neil Zhenqiang Gong, and Yang Zhang · 2021
Closest in time.
Membership Inference Attack on Graph Neural Networks
Iyiola E. Olatunji, Wolfgang Nejdl, and Megha Khosla · 2021
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