Research

Publications

  • Weimin Fu, Honggang Yu, Orlando Arias, Kaichen Yang, Yier Jin, Tuba Yavuz, Xiaolong Guo, ”Graph Neural Network based Hardware Trojan Detection at Intermediate Representative for SoC Platforms”, GLSVLSI 2022, 2022.(Accepted)

  • Max Panoff, Raj Gautam Dutta, Yaodan Hu, Kaichen Yang and Yier Jin, ”On Sensor Security in the Era of IoT and CPS”, SN Computer Science, 2021.

  • Kaichen Yang, Tzungyu-Tsai, Honggang Yu, Max Panoff, Tsung-yi Ho and Yier Jin, ”Robust Roadside Physical Adversarial Attack Against Deep Learning in Lidar Perception Modules”, 16th ACM ASIA Conference on Computerand Communications Security (ACM ASIACCS 2021). (19% acceptance ratio)

  • Kaichen Yang, Xuanyi-Lin, Yixi Sun, Tsung-Yi Ho and Yier Jin, ”3D-Adv: Black-Box Physical Adver- sarial Attacks against Deep Learning Models through 3D Sensors”, 58th Design Automation Conference (DAC), 2021. (To Appear) (23% acceptance ratio)

  • Honggang Yu, Haocheng Ma, Kaichen Yang, Yiqiang Zhao and Yier Jin, ”DeepEM: Deep Neural Net- works Model Recovery through EM Side-Channel Information Leakage”, IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2020.

  • Kaichen Yang, Tzungyu Tsai, Honggang Yu, Tsung-Yi Ho and Yier Jin, ”Beyond Digital Domain: Fool- ing Deep Learning Based Recognition System in Physical World”, Proceedings of the AAAI Conference on Artificial Intelligence, 2020. (20.6% acceptance ratio)

  • Tzungyu Tsai, Kaichen Yang, Tsung-Yi Ho and Yier Jin, ”Robust adversarial objects against deep learning models”, Proceedings of the AAAI Conference on Artificial Intelligence, 2020. Oral Presenta- tion. (20.6% acceptance ratio)

  • Honggang Yu, Kaichen Yang, Teng Zhang, Yun-Yun Tsai, Tsung-Yi Ho and Yier Jin, ”Cloudleak: Large-scale deep learning models stealing through adversarial examples”, Proceedings of Network and Distributed Systems SecuritySymposium (NDSS) /Blackhat USA, 2020. (17.4% acceptance ratio)

  • Kaichen Yang, Jianqing Liu, Chi Zhang and Yuguang Fang, ”Adversarial examples against the deep learning based network intrusion detection systems”, IEEE Military Communications Conference (MIL- COM), 2018.

  • Kaichen Yang, Chi Zhang and Nenghai Yu, ”Economic costs of multi-sever private information retrieval in cloudcomputing”, International Conference on Cloud Computing and Big Data (CCBD), 2015.

  • Mengke Yu, Kaichen Yang, Lingbo Wei and Jinyuan Sun, “Practical private information retrieval sup- porting keyword search in the cloud”, Sixth International Conference on Wireless Communications and Signal Processing (WCSP), 2014.

Presentations

Oral Presentations

  • “Adversarial examples against the deep learning based network intrusion detection systems”, in IEEE Military Communications Conference (MILCOM), Los Angeles, USA, Oct 2018

  • “Robust adversarial objects against deep learning models”, in AAAI Conference on Artificial Intelligence, New York, USA, Feb 2020

  • “Robust Roadside Physical Adversarial Attack Against Deep Learning in Lidar Perception Modules”, in ACM Asia Conference on Computer and Communications Security (AsiaCCS), Hongkong, China, June 2021

  • “3D-Adv: Black-Box Physical Adversarial Attacks against Deep Learning Models through 3D Sensors”, in Design Automation Conference (DAC), San Francisco, USA, Dec 2021

Poster Presentations

  • “Beyond Digital Domain: Fooling Deep Learning Based Recognition System in Physical World”, in AAAI Conference on Artificial Intelligence, New York, USA, Feb 2020

Projects

  • DoD-Intel State-of-the-Art Heterogeneous Integrated Packaging (SHIP) Prototype Project 2020 - 2022
  • STAMP Project 2020 - 2022