Publications


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Adversarial machine learning

  • Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng (Polo) Chau. ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2018. [Paper]

  • Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng Chau. Robust Physical Adversarial Attack on Faster R-CNN Object Detector. arXiv:1802.06816, April 2018. [Paper]

  • Weiyang Liu, Bo Dai, James M. Rehg, and Le Song. Iterative Machine Teaching. Appeared in International Conference on Machine Learning (ICML 2017). Sydney, Australia. August 2017. [Paper]

  • Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, and Le Song. SphereFace: Deep Hypersphere Embedding for Face Recognition. Appeared in CVPR 2017. Honolulu, Hawaii. July 2017. [Paper] [Results]

Adversarial-resillience

  • Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Li Chen, Michael E. Kounavis, Duen Horng (Polo) Chau. ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio. In Proceedings of ECML-PKDD (demo), 2018. [Paper]

  • Maria-Florina Balcan, Avrim Blum, Shang-Tse Chen. Diversified Strategies for Mitigating Adversarial Attacks in Multiagent Systems. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018. [Paper]

  • Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael E. Kounavis, Duen Horng Chau. Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2018. London, UK. Aug 19-23, 2018. [Paper] [Code]

  • Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael E. Kounavis, and Duen Horng Chau. Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression. arXiv:1705.02900, May 2017. [Paper]

MLSPLOIT

  • Steffen Maass, Changwoo Min, Sanidhya Kashyap, Woonhak Kang, Mohan Kumar, and Taesoo Kim. Mosaic: Processing a Trillion-Edge Graph on a Single Machine. In Proceedings of the 12st ACM European Conference on Computer Systems (EuroSys 2017). Belgrade, Serbia. April 2017. [Paper] [Slides]

Next-generation security analytics

  • Hong Hu, Chenxiong Qian, Carter Yagemann, Simon Pak Ho Chung, Bill Harris, Taesoo Kim and Wenke Lee. Enforcing Unique Code Target Property for Control-Flow Integrity. To appear in the 25th ACM Conference on Computer and Communications Security (CCS'18). Toronto, Canada. October 15-19, 2018.

  • Ren Ding, Chenxiong Qian, Chengyu Song, Bill Harris, Taesoo Kim, and Wenke Lee. Efficient Protection of Path-Sensitive Control Security. Appeared in Proceedings of the 26th USENIX Security Symposium (Security 2017). Vancouver, Canada. August 2017. [Paper]

Robust security analytics

  • Insu Yun, Sangho Lee, Meng Xu, Yeongjin Jang, and Taesoo Kim. QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing. To appear in Proceedings of the 27th USENIX Security Symposium (Security 2018). Baltimore, MD, August 2018.

  • Yang Ji, Sangho Lee, Mattia Fazzini, Joey Allen, Evan Downing, Taesoo Kim, Alessandro Orso, and Wenke Lee. Efficient Data Flow Tagging and Tracking for Refinable Cross-host Attack Investigation. To appear in Proceedings of the 27th USENIX Security Symposium (Security 2018). Baltimore, MD, August 2018.

  • Sanidhya Kashyap, Changwoo Min, and Taesoo Kim. Scaling Guest OS Critical Sections with eCS. To appear in Proceedings of the 2018 USENIX Annual Technical Conference (ATC 2018). Boston, MA, July 2018.

  • Meng Xu, Chenxiong Qian, Kangjie Lu, Michael Backes, and Taesoo Kim. Precise and Scalable Detection of Double-Fetch Bugs in OS Kernels. To appear in Proceedings of the 39th IEEE Symposium on Security and Privacy (S&P 2018). San Francisco, CA, May 2018. [Paper]

  • Sanidhya Kashyap, Changwoo Min, Kangnyeon Kim, and Taesoo Kim. A Scalable Ordering Primitive For Multicore Machines. In Proceedings of the 13rd ACM European Conference on Computer Systems (EuroSys 2018). Porto, Portugal, April, 2018. [Paper] [Slides]

  • Changwoo Min, Woon-Hak Kang, Mohan Kumar Sanidhya Kashyap, Steffen Maass, Heeseung Jo, and Taesoo Kim. SOLROS: A Data-Centric Operating System Architecture for Heterogeneous Computing. In Proceedings of the 13rd ACM European Conference on Computer Systems (EuroSys 2018). Porto, Portugal, April, 2018. [Paper] [Slides]

  • Mohan Kumar, Steffen Maass, Sanidhya Kashyap, Jan Vesely, Zi Yan, Taesoo Kim, Abhishek Bhattacharjee, and Tushar Krishna. LATR: Lazy Translation Coherence. In Proceedings of the 23rd ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2018). Williamsburg, VA, March, 2018. [Paper] [Slides]

  • Beumjin Cho, Sangho Lee, Meng Xu, Sangwoo Ji, Taesoo Kim, and Jong Kim. Prevention of Cross-update Privacy Leaks on Android. Appeared in Computer Science and Information Systems 15(1). January 2018. [Paper]

  • Yang Ji, Sangho Lee, Evan Downing, Weiren Wang, Mattia Fazzini, Taesoo Kim, Alessandro Orso, Wenke Lee. RAIN: Refinable Attack Investigation with On-demand Inter-Process Information Flow Tracking. Appeared in ACM Conference on Computer and Communications Security (CCS 2017). Dallas, USA. October 2017. [Paper]

  • Ruian Duan, Ashish Bijlani, Meng Xu, Taesoo Kim, Wenke Lee. Checking Open-Source License Violation and 1-day Security Risk at Large Scale. Appeared in ACM Conference on Computer and Communications Security (CCS 2017). Dallas, USA. October 2017. [Paper]

  • Wen Xu, Sanidhya Kashyap, Changwoo Min, Taesoo Kim. Designing New Operating Primitives to Improve Fuzzing Performance. Appeared in ACM Conference on Computer and Communications Security (CCS 2017). Dallas, USA. October 2017. [Paper]

  • Sangho Lee, Ming-Wei Shih, Prasun Gera, Taesoo Kim, Hyesoon Kim, and Marcus Peinado. Inferring Fine-grained Control Flow Inside SGX Enclaves with Branch Shadowing. Appeared in Proceedings of the 26th USENIX Security Symposium (Security 2017). Vancouver, Canada. August 2017. [Paper]

  • Jaehyuk Lee, Jinsoo Jang, Yeongjin Jang, Nohyun Kwak, Yeseul Choi, Changho Choi, Taesoo Kim, Marcus Peinado, and Brent B. Kang. Hacking in Darkness: Return-oriented Programming against Secure Enclaves. Appeared in Proceedings of the 26th USENIX Security Symposium (Security 2017). Vancouver, Canada. August 2017. [Paper]

  • Jinho Jung, Chanil Jeon, Max Wolotsky, Insu Yun, and Taesoo Kim. AVPASS: Leaking and Bypassing Antivirus Detection Model Automatically. Appeared in BlackHat USA 2017. Las Vegas, NV. Auguest 2017.

  • Seongmin Kim, Juhyeng Han, Jaehyeong Ha, Taesoo Kim, and Dongsu Han. Enhancing Security and Privacy of Tor's Ecosystem by using Trusted Execution Environments. In Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 2017). Boston, MA. March 2017. [Paper] [Slides] [Code]

  • Jaebaek Seo, Byoungyoung Lee, Sungmin Kim, Ming-Wei Shih, Insik Shin, Dongsu Han, and Taesoo Kim. SGX-Shield: Enabling Address Space Layout Randomization for SGX Programs. In Proceedings of the 2017 Network and Distributed System Security Symposium (NDSS 2017). San Diego, CA. February 2017. [Paper] [Slides]

  • Ming-Wei Shih, Sangho Lee, Taesoo Kim, and Marcus Peinado. T-SGX: Eradicating Controlled-Channel Attacks Against Enclave Programs. In Proceedings of the 2017 Network and Distributed System Security Symposium (NDSS 2017). San Diego, CA. February 2017. [Paper] [Slides] [Code]