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Knowledge graph reasoning (KGR) -- answering complex logical queries over large knowledge graphs -- represents an important artificial intelligence task, entailing a range of applications (e.g., cyber threat hunting).
Efficient Query Evaluation on Probabilistic Databases
Nilesh Dalvi and Dan Suciu · 2007
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Translating Embeddings for Modeling Multi-Relational Data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Durán, Jason Weston, and Oksana Yakhnenko · 2013
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Explaining and Harnessing Adversarial Examples
Ian Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Traversing Knowledge Graphs in Vector Space
Kelvin Guu, John Miller, and Percy Liang · 2015
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Learning to Represent Knowledge Graphs with Gaussian Embedding
Shizhu He, Kang Liu, Guoliang Ji, and Jun Zhao · 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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Understanding the Mirai Botnet
Manos Antonakakis, Tim April, Michael Bailey, Matt Bernhard, Elie Bursztein, Jaime Cochran, Zakir Durumeric, J. Alex Halderman, Luca Invernizzi, Michalis Kallitsis, Deepak Kumar, Chaz Lever, Zane Ma, Joshua Mason, Damian Menscher, Chad Seaman, Nick Sullivan, Kurt Thomas, and Yi Zhou · 2017
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Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini and David A. Wagner · 2017
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Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf and Max Welling · 2017
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Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye, Nicholas Carlini, and David Wagner · 2018
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Wild Patterns: Ten Years after The Rise of Adversarial Machine Learning
Battista Biggio and Fabio Roli · 2018
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AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation
Timon Gehr, Matthew Mirman, Dana Drachsler-Cohen, Petar Tsankov, Swarat Chaudhuri, and Martin Vechev · 2018
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Embedding Logical Queries on Knowledge Graphs
William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, and Jure Leskovec · 2018
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Systematically Understanding the Cyber Attack Business: A Survey
Keman Huang, Michael Siegel, and Stuart Madnick · 2018
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Model-Reuse Attacks on Deep Learning Systems
Yujie Ji, Xinyang Zhang, Shouling Ji, Xiapu Luo, and Ting Wang · 2018
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Trojaning Attack on Neural Networks
Yingqi Liu, Shiqing Ma, Yousra Aafer, Wen-Chuan Lee, Juan Zhai, Weihang Wang, and Xiangyu Zhang · 2018
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Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
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Turning Vice into Virtue: Using Batch-effects to Detect Errors in Large Genomic Data Sets
Fabrizio Mafessoni, Rashmi B Prasad, Leif Groop, Ola Hansson, and Kay Prüfer · 2018
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A Global Network of Biomedical Relationships Derived from Text
Bethany Percha and Russ B Altman · 2018
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Graph Attention Networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 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.
Kagnet: Knowledge-aware Graph Networks for Commonsense Reasoning
Bill Yuchen Lin, Xinyue Chen, Jamin Chen, and Xiang Ren · 2019
Cited alongside, same era.
DEEPSEC: A Uniform Platform for Security Analysis of Deep Learning Model
Xiang Ling, Shouling Ji, Jiaxu Zou, Jiannan Wang, Chunming Wu, Bo Li, and Ting Wang · 2019
Cited alongside, same era.
Holmes: Real-time APT Detection through Correlation of Suspicious Information Flows
Sadegh M Milajerdi, Rigel Gjomemo, Birhanu Eshete, Ramachandran Sekar, and VN Venkatakrishnan · 2019
Inductive Relation Prediction by Subgraph Reasoning
Komal Teru, Etienne Denis, and Will Hamilton · 2020
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Knowledge-driven drug repurposing using a comprehensive drug knowledge graph
Yongjun Zhu, Chao Che, Bo Jin, Ningrui Zhang, Chang Su, and Fei Wang · 2020
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https://www.gartner.com/en/newsroom/press-releases/2021-03-16-gartner-identifies-top-10-data-and-analytics-technologies-trends-for-2021
Gartner Identifies Top 10 Data and Analytics Technology Trends for 2021 · 2021
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Complex Query Answering with Neural Link Predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, and Michael Cochez · 2021
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Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods
Peru Bhardwaj, John Kelleher, Luca Costabello, and Declan O’Sullivan · 2021
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Cited alongside, same era.
Cyber-all-intel: An AI for Security Related Threat Intelligence
Sudip Mittal, Anupam Joshi, and Tim Finin · 2019
Cited alongside, same era.
Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications
Pouya Pezeshkpour, Yifan Tian, and Sameer Singh · 2019
Cited alongside, same era.
Attacking Graph-based Classification via Manipulating the Graph Structure
Binghui Wang and Neil Zhenqiang Gong · 2019
Cited alongside, same era.
Explainable Reasoning over Knowledge Graphs for Recommendation
Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, and Tat-Seng Chua · 2019
Cited alongside, same era.
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective
Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, and Xue Lin · 2019
Cited alongside, same era.
Data Poisoning Attack against Knowledge Graph Embedding
Hengtong Zhang, Tianhang Zheng, Jing Gao, Chenglin Miao, Lu Su, Yaliang Li, and Kui Ren · 2019
Cited alongside, same era.
Peru Bhardwaj, John Kelleher, Luca Costabello, and Declan O’Sullivan · 2021
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Enabling Efficient Cyber Threat Hunting with Cyber Threat Intelligence
Peng Gao, Fei Shao, Xiaoyuan Liu, Xusheng Xiao, Zheng Qin, Fengyuan Xu, Prateek Mittal, Sanjeev R Kulkarni, and Dawn Song · 2021
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SMR: Medical Knowledge Graph Embedding for Safe Medicine Recommendation
Fan Gong, Meng Wang, Haofen Wang, Sen Wang, and Mengyue Liu · 2021
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Toward a Knowledge Graph of Cybersecurity Countermeasures
Peter E Kaloroumakis and Michael J Smith · 2021
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Combating Fake Cyber Threat Intelligence Using Provenance in Cybersecurity Knowledge Graphs
Shaswata Mitra, Aritran Piplai, Sudip Mittal, and Anupam Joshi · 2021
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Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
Mrigank Raman, Aaron Chan, Siddhant Agarwal, Peifeng Wang, Hansen Wang, Sungchul Kim, Ryan Rossi, Handong Zhao, Nedim Lipka, and Xiang Ren · 2021
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Generating Fake Cyber Threat Intelligence Using Transformer-based Models
Priyanka Ranade, Aritran Piplai, Sudip Mittal, Anupam Joshi, and Tim Finin · 2021
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LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, and Denny Zhou · 2021
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Graph backdoor
Zhaohan Xi, Ren Pang, Shouling Ji, and Ting Wang · 2021
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Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard A Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, and Fabio Roli · 2022
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Towards Certifying the Asymmetric Robustness for Neural Networks: Quantification and Applications
Changjiang Li, Shouling Ji, Haiqin Weng, Bo Li, Jie Shi, Raheem Beyah, Shanqing Guo, Zonghui Wang, and Ting Wang · 2022
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Demystifying Self-supervised Trojan Attacks
Changjiang Li, Ren Pang, Zhaohan Xi, Tianyu Du, Shouling Ji, Yuan Yao, and Ting Wang · 2022
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A Knowledge Graph to Interpret Clinical Proteomics Data
Alberto Santos, Ana R Colaço, Annelaura B Nielsen, Lili Niu, Maximilian Strauss, Philipp E Geyer, Fabian Coscia, Nicolai J Wewer Albrechtsen, Filip Mundt, Lars Juhl Jensen, et al · 2022
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Poisoning Web-Scale Training Datasets is Practical
Nicholas Carlini, Matthew Jagielski, Christopher A Choquette-Choo, Daniel Paleka, Will Pearce, Hyrum Anderson, Andreas Terzis, Kurt Thomas, and Florian Tramèr · 2023
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