Ka-Ho Chow

Assistant Professor
Department of Computer Science
The University of Hong Kong (HKU)
Email: kachow@cs.hku.hk
Office: CB-403, Chow Yei Ching Building, Pok Fu Lam Rd, Hong Kong

News

  • Apr 2024 One paper on efficient privacy attacks in federated learning accepted by CVPRW 2024
  • Apr 2024 A preprint on robust few-shot learning is released on arXiv
  • Feb 2024 A survey on privacy threats in vertical federated learning is released on arXiv
  • Jan 2024 One paper on LLM for blockchain security accepted by WWW 2024
  • Jan 2024 A preprint on LLM for backdoor attacks is released on arXiv
  • Dec 2023 One paper on data poisoning attacks accepted by IEEE TSC
  • Oct 2023 One paper on efficient neural network inference accepted by WACV 2024
  • Oct 2023 One paper on ensemble learning accepted by ACM TIST
  • Sep 2023 One paper on backdoor-resilient federated learning accepted by NeurIPS 2023
  • Sep 2023 One paper on data breach detection and hybrid cloud migration for microservices accepted by EuroSys 2024
  • Sep 2023 Two papers on defenses against gradient leakage attacks and adversarial attacks accepted by ICDM 2023
  • May 2023 One paper on gradient leakage-resilient federated learning accepted by IEEE TPDS
  • Mar 2023 One paper on efficient neural network inference accepted by WWW 2023
  • Feb 2023 One paper on hijacking-resilient federated learning accepted by CVPR 2023
  • Feb 2023 One paper on scaling microservices with hybrid clouds accepted by SIGMOD 2023
  • Aug 2022 One paper on error diversity-driven ensembles for robust object detection accepted by ICDM 2022
  • May 2022 Awarded the IBM PhD Fellowship 2022
  • Apr 2022 One paper on local differential privacy accepted by IEEE TIFS
  • Feb 2022 Received the travel award to attend EuroSys 2022
  • Jan 2022 One paper on ransomware and cryptojacking detection for microservices accepted by EuroSys 2022
  • [More]

Ka-Ho Chow

The University of Hong Kong (HKU)

I am an Assistant Professor in the Department of Computer Science at the University of Hong Kong (HKU). I was named an IBM PhD Fellow in 2022 and a Croucher Scholar in 2021. Before joining HKU, I was a research scientist at IBM Research and received my Ph.D. in Computer Science from the Georgia Institute of Technology (Georgia Tech), advised by Prof. Ling Liu.

My research interests are at the intersection of machine learning, cybersecurity, and systems. The overarching goal is to amplify the real-world impact of artificial intelligence by building trustworthy and scalable technologies. To this end, my recent work focuses on (i) understanding new security and privacy threats to AI systems, (ii) developing attack-resilient solutions, and (iii) enhancing scalability through algorithmic and infrastructure optimization. These efforts span various learning approaches, including centralized and federated learning, and cover a range of applications across, e.g., large language models and visual recognition.

Research Interests

Trustworthy AI Systems; Cybersecurity; ML for Systems & Systems for ML

Selected Publications

[Google Scholar] [DBLP]
  • PREPRINT Ka-Ho Chow, Wenqi Wei, and Lei Yu, "Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control," arXiv preprint arXiv:2401.01085, Jan. 2, 2024. [PDF] [CODE]
  • PREPRINT Lei Yu, Meng Han, Yiming Li, Changting Lin, Yao Zhang, Mingyang Zhang, Yan Liu, Haiqin Weng, Yuseok Jeon, Ka-Ho Chow, and Stacy Patterson, "A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective," arXiv preprint arXiv:2402.03688, Feb 6, 2024. [PDF]
  • CVPRW 2024 Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang, Wenbin Zhang, and Yanzhao Wu, "On the Efficiency of Privacy Attacks in Federated Learning," IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops - FedVision (CVPRW), Seattle, WA, USA, Jun. 17-21, 2024.
  • WWW 2024 Sihao Hu, Tiansheng Huang, Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, and Ling Liu, "ZipZap: Efficient Training of Language Models for Ethereum Fraud Detection," The Web Conference (WWW), Singapore, May 13-17, 2024. [PDF] [CODE]
  • EuroSys 2024 Ka-Ho Chow, Umesh Deshpande, Veera Deenadhayalan, Sangeetha Seshadri, and Ling Liu, "Atlas: Hybrid Cloud Migration Advisor for Interactive Microservices," ACM European Conference on Computer Systems (EuroSys), Athens, Greece, Apr. 22-25, 2024. [PDF] [CODE]
  • WACV 2024 Fatih Ilhan, Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Selim Furkan Tekin, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu, and Ling Liu, "Adaptive Deep Neural Network Inference Optimization with EENet," IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, USA, Jan 4-8, 2024. [CODE]
  • NeurIPS 2023 Tiansheng Huang, Sihao Hu, Ka-Ho Chow, Fatih Ilhan, Selim Furkan Tekin, and Ling Liu, "Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training," Neural Information Processing Systems (NeurIPS), New Orleans, LA, USA, Dec 10-16, 2023. [PDF] [CODE]
  • ICDM 2023 Wenqi Wei, Ka-Ho Chow, Fatih Ilhan, Yanzhao Wu, and Ling Liu, "Model Cloaking against Gradient Leakage," IEEE International Conference on Data Mining (ICDM), Shanghai, China, Dec 1-4, 2023. [CODE]
  • ICDM 2023 Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, and Ling Liu, "Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness," IEEE International Conference on Data Mining (ICDM), Shanghai, China, Dec 1-4, 2023. [PDF] [CODE]
  • CVPR 2023 Ka-Ho Chow, Ling Liu, Wenqi Wei, Fatih Ilhan, and Yanzhao Wu, "STDLens: Model Hijacking-Resilient Federated Learning for Object Detection," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, Jun. 18-22, 2023. [PDF]
  • SIGMOD 2023 Ka-Ho Chow, Umesh Deshpande, Veera Deenadhayalan, Sangeetha Seshadri, and Ling Liu, "SCAD: Scalability Advisor for Interactive Microservices on Hybrid Clouds," ACM SIGMOD International Conference on Management of Data (SIGMOD), Seattle, WA, USA, Jun. 18-23, 2023. [PDF] 🎮 Demo
  • ICDM 2022 Ka-Ho Chow and Ling Liu, "Boosting Object Detection Ensembles with Error Diversity," IEEE International Conference on Data Mining (ICDM), Orlando, FL, USA, Nov. 28 - Dec. 1, 2022. [PDF] [CODE]
  • EuroSys 2022 Ka-Ho Chow, Umesh Deshpande, Sangeetha Seshadri, and Ling Liu, "DeepRest: Deep Resource Estimation for Interactive Microservices," ACM European Conference on Computer Systems (EuroSys), Rennes, France, Apr. 5-8, 2022. [PDF] [CODE]
  • SIGKDD 2021 Ka-Ho Chow and Ling Liu, "Robust Object Detection Fusion Against Deception," ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), Singapore, Aug. 14-18, 2021. [PDF] [CODE]
  • SIGMOD 2021 Ka-Ho Chow, Umesh Deshpande, Sangeetha Seshadri, and Ling Liu, "SRA: Smart Recovery Advisor for Cyber Attacks," ACM SIGMOD International Conference on Management of Data (SIGMOD), Xi'an, Shaanxi, China, Jun. 20-25, 2021. [PDF] 🎮 Demo
  • CVPR 2021 Yanzhao Wu, Ling Liu, Zhongwei Xie, Ka-Ho Chow, and Wenqi Wei, "Boosting Ensemble Accuracy by Revisiting Ensemble Diversity Metrics," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, Jun. 19-25, 2021. [PDF] [CODE]
  • ESORICS 2020 Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, and Yanzhao Wu, "Understanding Object Detection Through An Adversarial Lens," European Symposium on Research in Computer Security (ESORICS), Guildford, United Kingdom, Sep. 14-18, 2020. [PDF] [CODE] 🎮 Demo
  • ESORICS 2020 Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, and Yanzhao Wu, "A Framework for Evaluating Gradient Leakage Attacks in Federated Learning," European Symposium on Research in Computer Security (ESORICS), Guildford, United Kingdom, Sep. 14-18, 2020. [PDF] [CODE] 🎮 Demo
  • BigData 2019 Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, and Ling Liu, "Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks," IEEE International Conference on Big Data (BigData), Los Angeles, CA, USA, Dec. 9-12, 2019. [PDF]
  • TSC Wenqi Wei, Ka-Ho Chow, Yanzhao Wu, and Ling Liu, "Demystifying Data Poisoning Attacks in Distributed Learning as a Service," IEEE Transactions on Services Computing (TSC), Vol. 17, No. 1, pp. 237-250, February 2024.
  • TIST Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, and Ling Liu, "Hierarchical Pruning of Deep Ensembles with Focal Diversity," ACM Transactions on Intelligent Systems and Technology (TIST), Vol. 15, No. 15, pp. 1-24, January 2024. [PDF] [CODE]
  • TPDS Wenqi Wei, Ling Liu, Jingya Zhou, Ka-Ho Chow, and Yanzhao Wu, "Securing Distributed SGD against Gradient Leakage Threats," IEEE Transactions on Parallel and Distributed Systems (TPDS), Vol. 34, No. 7, pp. 2040-2054, July 2023. [PDF] [CODE]
  • TMC Jiajie Tan, Hang Wu, Ka-Ho Chow, and Shueng-Han Gary Chan, "Implicit Multimodal Crowdsourcing for Joint RF and Geomagnetic Fingerprinting," IEEE Transactions on Mobile Computing (TMC), Vol. 22, No. 2, pp. 935-950, February 2023. [PDF]
  • TIFS Mehmet Emre Gursoy, Ling Liu, Ka-Ho Chow, Stacey Truex, and Wenqi Wei, "An Adversarial Approach to Protocol Analysis and Selection in Local Differential Privacy," IEEE Transactions on Information Forensics and Security (TIFS), Vol. 17, pp. 1785-1799, May 2022. [PDF]
  • TMC Ka-Ho Chow, Suining He, Jiajie Tan, and Shueng-Han Gary Chan, "Efficient Locality Classification for Indoor Fingerprint-based Systems," IEEE Transactions on Mobile Computing (TMC), Vol. 18, No. 2, pp. 290-304, February 2019. [PDF]

Full Publication List

[Show]

Awards and Achievements

  • IBM Patent File Award, 2024
  • IBM PhD Fellowship, 2022
  • Travel Award, ACM European Conference on Computer Systems, 2022
  • Croucher Scholarship, Croucher Foundation, Hong Kong, 2021
  • Best Paper Award, ACM International Workshop on Edge Systems, Analytics and Networking, 2020
  • Travel Award, IEEE International Conference on Big Data, 2019
  • Chair's Fellowship, Georgia Tech, 2019
  • Postgraduate Studentship, HKUST, 2016-2018
  • Dean's List, HKUST, 2015-2016
  • Hang Lung: Chan Tseng-Hsi Scholarship, Hong Kong, 2013-2014
  • Sir Edward Youde Memorial Prize, Hong Kong, 2009-2010

Presentations

  • Upcoming ACM European Conference on Computer Systems, Athens, Greece, Apr. 22-25, 2024.
  • IBM Hybrid Cloud Infrastructure Research Seminar, Virtual Seminar, Aug. 23 & Sep. 13, 2023.
  • IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, Canada, Jun. 18-22, 2023.
  • ACM SIGMOD International Conference on Management of Data, Seattle, WA, USA, Jun. 18-23, 2023.
  • IEEE International Conference on Data Mining, Orlando, FL, USA, Nov. 28 - Dec. 1, 2022.
  • ACM European Conference on Computer Systems, Rennes, France, Apr. 5-8, 2022.
  • IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications, Virtual Conference, Dec. 13-15, 2021.
  • ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Singapore, Aug. 14-18, 2021.
  • ACM SIGMOD International Conference on Management of Data, Xi'an, Shaanxi, China, Jun. 20-25, 2021.
  • IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications, Atlanta, GA, USA, Dec. 1-3, 2020.
  • European Symposium on Research in Computer Security, Guildford, United Kingdom, Sep. 14-18, 2020.
  • IEEE International Conference on Cognitive Machine Intelligence, Los Angeles, CA, USA, Dec. 12-14, 2019.
  • IEEE International Conference on Big Data, Los Angeles, CA, USA, Dec. 9-12, 2019.
  • Cybersecurity Summit, Institute for Information Security & Privacy, Atlanta, GA, USA, Sep. 10, 2019.

Academic Services

  • Conference Reviewer: CVPR (2021, 2022, 2023, 2024), AAAI (2022, 2023, 2024), IJCAI (2024), ECCV (2022, 2024), TheWebConf (2024), WACV (2024), SIGKDD (2022, 2023, 2024), MASS (2024), SDM (2024), EuroSys (2024), CLOUD (2024), ICCV (2023), SIGSPATIAL (2023), ML4H (2020, 2021, 2022, 2023), HiPC (2023), HPDC (2022), TS4H (2022), Middleware (2021), INFOCOM (2017, 2018)
  • Journal Reviewer: IEEE TIFS, IEEE TMC, IEEE TCC, ACM TOIT