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Graph data, such as chemical networks and social networks, may be deemed confidential/private because the data owner often spends lots of resources collecting the data or the data contains sensitive information, e.g., social relationships.
Distinguishing Enzyme Structures from Non-Enzymes without Alignments
Paul D. Dobson and Andrew J. Doig · 2003
Earlier work this paper cites.
SplineFitting with a Genetic Algorithm: A Method for Developing Classification Structure Activity Relationships
Jeffrey Sutherland, Lee O’Brien, and Donald Weaver · 2003
Earlier work this paper cites.
Protein Function Prediction via Graph Kernels
Karsten M. Borgwardt, Cheng Soon Ong, Stefan Schönauer, S. V. N. Vishwanathan, Alexander J. Smola, and Hans-Peter Kriegel · 2005
Earlier work this paper cites.
The Link-prediction Problem for Social Networks
David Liben-Nowell and Jon Kleinberg · 2007
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Structural, Syntactic, and Statistical Pattern Recognition
Kaspar Riesen and Horst Bunke · 2008
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Visualizing Data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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Accurate Estimation of the Degree Distribution of Private Networks
Michael Hay, Chao Li, Gerome Miklau, and David D. Jensen · 2009
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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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Joint Link Prediction and Attribute Inference Using a Social-Attribute Network
Neil Zhenqiang Gong, Ameet Talwalkar, Lester W. Mackey, Ling Huang, Eui Chul Richard Shin, Emil Stefanov, Elaine Shi, and Dawn Song · 2014
Earlier work this paper cites.
Will This Paper Increase Your h -index?: Scientific Impact Prediction
Yuxiao Dong, Reid A. Johnson, and Nitesh V. Chawla · 2015
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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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Private Release of Graph Statistics using Ladder Functions
Jun Zhang, Graham Cormode, Cecilia M. Procopiuc, Divesh Srivastava, and Xiaokui Xiao · 2015
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Diffusion-Convolutional Neural Networks
James Atwood and Don Towsley · 2016
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Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
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You are Who You Know and How You Behave: Attribute Inference Attacks via Users’ Social Friends and Behaviors
Neil Zhenqiang Gong and Bin Liu · 2016
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node2vec: Scalable Feature Learning for Networks
Aditya Grover and Jure Leskovec · 2016
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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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Practical Attacks Against Graph-based Clustering
Yizheng Chen, Yacin Nadji, Athanasios Kountouras, Fabian Monrose, Roberto Perdisci, Manos Antonakakis, and Nikolaos Vasiloglou · 2017
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Neural Message Passing for Quantum Chemistry
Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, and George E. Dahl · 2017
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Inductive Representation Learning on Large Graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf and Max Welling · 2017
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DeepCity: A Feature Learning Framework for Mining Location Check-Ins
Jun Pang and Yang Zhang · 2017
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Quantifying Location Sociality
Jun Pang and Yang Zhang · 2017
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Practical Black-Box Attacks Against Machine Learning
Nicolas Papernot, Patrick D. McDaniel, Ian Goodfellow, Somesh Jha, Z. Berkay Celik, and Ananthram Swami · 2017
Earlier work this paper cites.
Membership Inference Attacks Against Machine Learning Models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017
Cited alongside, same era.
Differentially Private Data Generative Models
Qingrong Chen, Chong Xiang, Minhui Xue, Bo Li, Nikita Borisov, Dali Kaarfar, and Haojin Zhu · 2018
Cited alongside, same era.
Adversarial Attack on Graph Structured Data
Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, and Le Song · 2018
Cited alongside, same era.
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning
Jinyuan Jia and Neil Zhenqiang Gong · 2018
Cited alongside, same era.
Machine Learning with Membership Privacy using Adversarial Regularization
Milad Nasr, Reza Shokri, and Amir Houmansadr · 2018
Cited alongside, same era.
Auditing Data Provenance in Text-Generation Models
Congzheng Song and Vitaly Shmatikov · 2019
Later among the works it cites.
Attacking Graph-based Classification via Manipulating the Graph Structure
Binghui Wang and Neil Zhenqiang Gong · 2019
Later among the works it cites.
Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation
Binghui Wang, Jinyuan Jia, and Neil Zhenqiang Gong · 2019
Later among the works it cites.
Adversarial Examples for Graph Data: Deep Insights into Attack and Defense
Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, and Liming Zhu · 2019
Later among the works it cites.
Language in Our Time: An Empirical Analysis of Hashtags
Yang Zhang · 2019
Later among the works it cites.
Robust Graph Convolutional Networks Against Adversarial Attacks
Dingyuan Zhu, Ziwei Zhang, Peng Cui, and Wenwu Zhu · 2019
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Nicolas Papernot, Patrick McDaniel, Arunesh Sinha, and Michael Wellman · 2018
Cited alongside, same era.
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
Ali Shafahi, W Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, and Tom Goldstein · 2018
Cited alongside, same era.
Graph Attention Networks
Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
Cited alongside, same era.
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
Aleksandar Bojchevski and Stephan Günnemann · 2019
Cited alongside, same era.
Later among the works it cites.
Adversarial Attacks on Graph Neural Networks via Meta Learning
Daniel Zügner and Stephan Günnemann · 2019
Later among the works it cites.
Certifiable Robustness and Robust Training for Graph Convolutional Networks
Daniel Zügner and Stephan Günnemann · 2019
Later among the works it cites.
Exploring Connections Between Active Learning and Model Extraction
Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, and Songbai Yan · 2020
Closest in time.
GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs
Dingfan Chen, Ning Yu, Yang Zhang, and Mario Fritz · 2020
Closest in time.
When Machine Unlearning Jeopardizes Privacy
Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, and Yang Zhang · 2020
Closest in time.
On Training Robust PDF Malware Classifiers
Yizheng Chen, Shiqi Wang, Dongdong She, and Suman Jana · 2020
Closest in time.
Benchmarking Graph Neural Networks
Vijay Prakash Dwivedi, Chaitanya K. Joshi, Thomas Laurent, Yoshua Bengio, and Xavier Bresson · 2020
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A Fair Comparison of Graph Neural Networks for Graph Classification
Federico Errica, Marco Podda, Davide Bacciu, and Alessio Micheli · 2020
Closest in time.
High Accuracy and High Fidelity Extraction of Neural Networks
Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, and Nicolas Papernot · 2020
Closest in time.
Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing
Jinyuan Jia, Binghui Wang, Xiaoyu Cao, and Neil Zhenqiang Gong · 2020
Closest in time.
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference
Klas Leino and Matt Fredrikson · 2020
Closest in time.
Shaofeng Li, Shiqing Ma, Minhui Xue, and Benjamin Zi Hao Zhao · 2020
Closest in time.
Label-Leaks: Membership Inference Attack with Label
Zheng Li and Yang Zhang · 2020
Closest in time.
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks
Tribhuvanesh Orekondy, Bernt Schiele, and Mario Fritz · 2020
Closest in time.
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning
Ahmed Salem, Apratim Bhattacharya, Michael Backes, Mario Fritz, and Yang Zhang · 2020
Closest in time.
Dynamic Backdoor Attacks Against Machine Learning Models
Ahmed Salem, Rui Wen, Michael Backes, Shiqing Ma, and Yang Zhang · 2020
Closest in time.
Robust Membership Encoding: Inference Attacks and Copyright Protection for Deep Learning
Congzheng Song and Reza Shokri · 2020
Closest in time.
Towards Plausible Graph Anonymization
Yang Zhang, Mathias Humbert, Bartlomiej Surma, Praveen Manoharan, Jilles Vreeken, and Michael Backes · 2020
Closest in time.
Backdoor Attacks to Graph Neural Networks
Zaixi Zhang, Jinyuan Jia, Binghui Wang, and Neil Zhenqiang Gong · 2020
Closest in time.