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Sanghyun Hong
Sanghyun Hong
Assistant Professor, Oregon State University
Verified email at oregonstate.edu - Homepage
Title
Cited by
Cited by
Year
Shallow-deep networks: Understanding and mitigating network overthinking
Y Kaya, S Hong, T Dumitras
International conference on machine learning, 3301-3310, 2019
2182019
Terminal Brain Damage: Exposing the Graceless Degradation in Deep Neural Networks Under Hardware Fault Attacks
S Hong, P Frigo, Y Kaya, C Giuffrida, T Dumitraş
28th USENIX Security Symposium (USENIX Security 19). Santa Clara, CA: USENIX …, 2019
1642019
On the effectiveness of mitigating data poisoning attacks with gradient shaping
S Hong, V Chandrasekaran, Y Kaya, T Dumitraş, N Papernot
arXiv preprint arXiv:2002.11497, 2020
882020
Security analysis of deep neural networks operating in the presence of cache side-channel attacks
S Hong, M Davinroy, Y Kaya, SN Locke, I Rackow, K Kulda, ...
arXiv preprint arXiv:1810.03487, 2018
602018
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets
F Tramèr, R Shokri, AS Joaquin, H Le, M Jagielski, S Hong, N Carlini
ACM Conference on Computer and Communications Security (CCS), 2022
432022
Go serverless: Securing cloud via serverless design patterns
S Hong, A Srivastava, W Shambrook, T Dumitraș
10th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 18), 2018
422018
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
S Hong, Y Kaya, IV Modoranu, T Dumitraş
9th International Conference on Learning Representations (ICLR 2021)., 2021
342021
Handcrafted backdoors in deep neural networks
S Hong, N Carlini, A Kurakin
Advances in Neural Information Processing Systems 35, 8068-8080, 2022
322022
How to 0wn NAS in Your Spare Time
S Hong, M Davinroy, Y Kaya, D Dachman-Soled, T Dumitraş
8th International Conference on Learning Representations (ICLR 2020)., 2020
322020
Data Poisoning Won't Save You From Facial Recognition
E Radiya-Dixit, S Hong, N Carlini, F Tramèr
10th International Conference on Learning Representations (ICLR 2022)., 2022
302022
Summoning demons: The pursuit of exploitable bugs in machine learning
R Stevens, O Suciu, A Ruef, S Hong, M Hicks, T Dumitraş
arXiv preprint arXiv:1701.04739, 2017
212017
On the effectiveness of regularization against membership inference attacks
Y Kaya, S Hong, T Dumitras
arXiv preprint arXiv:2006.05336, 2020
202020
Page: Answering graph pattern queries via knowledge graph embedding
S Hong, N Park, T Chakraborty, H Kang, S Kwon
International Conference on Big Data, 87-99, 2018
92018
Qu-anti-zation: Exploiting quantization artifacts for achieving adversarial outcomes
S Hong, MA Panaitescu-Liess, Y Kaya, T Dumitras
Advances in Neural Information Processing Systems 34, 9303-9316, 2021
82021
Improving Cross-platform Binary Analysis Using Representation Learning via Graph Alignment
G Kim, S Hong, M Franz, D Song
Proceedings of the 31st ACM SIGSOFT International Symposium on Software …, 2022
62022
Certified Malware in South Korea: A Localized Study of Breaches of Trust in Code-Signing PKI Ecosystem
B Kwon, S Hong, Y Jeon, D Kim
Information and Communications Security: 23rd International Conference …, 2021
52021
SENA: preserving social structure for network embedding
S Hong, T Chakraborty, S Ahn, G Husari, N Park
Proceedings of the 28th ACM Conference on hypertext and social media, 235-244, 2017
52017
Peek-a-boo: Inferring program behaviors in a virtualized infrastructure without introspection
S Hong, A Nicolae, A Srivastava, T Dumitraş
Computers & Security 79, 190-207, 2018
42018
A scanner deeply: Predicting gaze heatmaps on visualizations using crowdsourced eye movement data
S Shin, S Chung, S Hong, N Elmqvist
IEEE Transactions on Visualization and Computer Graphics 29 (1), 396-406, 2022
32022
AdamNODEs: When Neural ODE Meets Adaptive Moment Estimation
S Cho, S Hong, K Lee, N Park
International Conference on Machine Learning (ICML) Workshop on Continuous …, 2022
22022
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Articles 1–20