Overview
Background
Dr Guangdong Bai is an Associate Professor at School of Electrical Engineering and Computer Science, The University of Queensland, Australia. His research interests include Cyber Security, Software Engineering and Formal Methods.
He obtained his PhD degree from National University of Singapore, Singapore, and M.S. and B.S. degrees from Peking University, China.
Please visit his webpage for latest update: https://baigd.github.io/
Availability
- Associate Professor Guangdong Bai is:
- Available for supervision
Qualifications
- Doctor of Philosophy, National University of Singapore
Research interests
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Mobile Security, Software Security, Internet of Things (IoT) Security
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Protocol Verification
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Software Engineering
Works
Search Professor Guangdong Bai’s works on UQ eSpace
2024
Conference Publication
Exploring ChatGPT App Ecosystem: Distribution, Deployment and Security
Yan, Chuan, Ren, Ruomai, Meng, Mark Huasong, Wan, Liuhuo, Ooi, Tian Yang and Bai, Guangdong (2024). Exploring ChatGPT App Ecosystem: Distribution, Deployment and Security. New York, NY, USA: ACM. doi: 10.1145/3691620.3695510
2024
Conference Publication
Unveiling Intellectual Property Vulnerabilities of GAN-Based Distributed Machine Learning through Model Extraction Attacks
Ma, Mengyao, Liu, Shuofeng, M.A.P. Chamikara, , Baruwal Chhetri, Mohan and Bai, Guangdong (2024). Unveiling Intellectual Property Vulnerabilities of GAN-Based Distributed Machine Learning through Model Extraction Attacks. New York, NY, USA: ACM. doi: 10.1145/3627673.3679850
2024
Conference Publication
Large Language Models Can Connect the Dots: Exploring Model Optimization Bugs with Domain Knowledge-Aware Prompts
Guan, Hao, Bai, Guangdong and Liu, Yepang (2024). Large Language Models Can Connect the Dots: Exploring Model Optimization Bugs with Domain Knowledge-Aware Prompts. New York, NY, USA: ACM. doi: 10.1145/3650212.3680383
2024
Journal Article
DeeBBAA: a benchmark deep black box adversarial attack against cyber-physical power systems
Bhattacharjee, Arnab, Bai, Guangdong, Tushar, Wayes, Verma, Ashu, Mishra, Sukumar and Saha, Tapan K. (2024). DeeBBAA: a benchmark deep black box adversarial attack against cyber-physical power systems. IEEE Internet of Things Journal, 1-1. doi: 10.1109/jiot.2024.3454257
2024
Journal Article
Investigating Documented Privacy Changes in Android OS
Yan, Chuan, Meng, Mark Huasong, Xie, Fuman and Bai, Guangdong (2024). Investigating Documented Privacy Changes in Android OS. Proceedings of the ACM on Software Engineering, 1 (FSE), 2701-2724. doi: 10.1145/3660826
2024
Conference Publication
Universal adversarial perturbations for vision-language pre-trained models
Zhang, Peng-Fei, Huang, Zi and Bai, Guangdong (2024). Universal adversarial perturbations for vision-language pre-trained models. 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657781
2024
Conference Publication
AuSSE: a novel framework for security and safety evaluation for autonomous vehicles
Nguyen, Nhung H., Cho, Jin-Hee, Moore, Terrence J., Yoon, Seunghyun, Lim, Hyuk, Nelson, Frederica, Bai, Guangdong and Kim, Dan Dongseong (2024). AuSSE: a novel framework for security and safety evaluation for autonomous vehicles. 2024 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, Brisbane, QLD, Australia, 24-27 June 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/dsn-s60304.2024.00012
2024
Conference Publication
PANDA: Practical Adversarial Attack Against Network Intrusion Detection
Swain, Subrat Kumar, Kumar, Vireshwar, Bai, Guangdong and Kim, Dan Dongseong (2024). PANDA: Practical Adversarial Attack Against Network Intrusion Detection. 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), Brisbane, QLD, Australia, 24-27 June 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/dsn-s60304.2024.00017
2024
Journal Article
Beyond Fidelity: Explaining Vulnerability Localization of Learning-Based Detectors
Cheng, Baijun, Zhao, Shengming, Wang, Kailong, Wang, Meizhen, Bai, Guangdong, Feng, Ruitao, Guo, Yao, Ma, Lei and Wang, Haoyu (2024). Beyond Fidelity: Explaining Vulnerability Localization of Learning-Based Detectors. ACM Transactions on Software Engineering and Methodology, 33 (5) 127, 1-33. doi: 10.1145/3641543
2024
Journal Article
Tryptophan metabolism and piglet diarrhea: Where we stand and the challenges ahead
Zhao, Xuan, Pang, Jiaman, Zhang, Wanghong, Peng, Xie, Yang, Zhenguo, Bai, Guangdong and Xia, Yaoyao (2024). Tryptophan metabolism and piglet diarrhea: Where we stand and the challenges ahead. Animal Nutrition, 17, 123-133. doi: 10.1016/j.aninu.2024.03.005
2024
Conference Publication
CORELOCKER: neuron-level usage control
Wang, Zihan, Ma, Zhongkui, Feng, Xinguo, Sun, Ruoxi, Wang, Hu, Xue, Minhui and Bai, Guangdong (2024). CORELOCKER: neuron-level usage control. 2024 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, United States, 19-23 May 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/sp54263.2024.00233
2024
Conference Publication
Is it safe to share your files? An empirical security analysis of Google workspace
Wan, Liuhuo, Wang, Kailong, Wang, Haoyu and Bai, Guangdong (2024). Is it safe to share your files? An empirical security analysis of Google workspace. ACM Web Conference 2024, Singapore, Singapore, 13-17 May 2024. New York, NY, United States: ACM. doi: 10.1145/3589334.3645697
2024
Conference Publication
Don't bite off more than you can chew: investigating excessive permission requests in trigger-action integrations
Wan, Liuhuo, Wang, Kailong, Mahadewa, Kulani, Wang, Haoyu and Bai, Guangdong (2024). Don't bite off more than you can chew: investigating excessive permission requests in trigger-action integrations. WWW '24: ACM Web Conference 2024, Singapore, Singapore, 13–17 May 2024. New York, NY, United States: ACM. doi: 10.1145/3589334.3645721
2024
Conference Publication
Privacy-preserving and fairness-aware federated learning for critical infrastructure protection and resilience
Zhang, Yanjun, Sun, Ruoxi, Shen, Liyue, Bai, Guangdong, Xue, Minhui, Meng, Mark Huasong, Li, Xue, Ko, Ryan and Nepal, Surya (2024). Privacy-preserving and fairness-aware federated learning for critical infrastructure protection and resilience. WWW '24: ACM Web Conference 2024, Singapore, Singapore, 13-17 May 2024. New York, NY, United States: ACM. doi: 10.1145/3589334.3645545
2024
Conference Publication
Are your requests your true needs? Checking excessive data collection in VPA App
Xie, Fuman, Yan, Chuan, Meng, Mark Huasong, Teng, Shaoming, Zhang, Yanjun and Bai, Guangdong (2024). Are your requests your true needs? Checking excessive data collection in VPA App. ICSE '24: IEEE/ACM 46th International Conference on Software Engineering, Lisbon, Portugal, 14-20 April 2024. New York, NY, United States: ACM. doi: 10.1145/3597503.3639107
2024
Conference Publication
Symbolic verification of mesh commissioning protocol of thread
Upadhyay, Pankaj, Sharma, Subodh and Bai, Guangdong (2024). Symbolic verification of mesh commissioning protocol of thread. 17th Innovations in Software Engineering Conference (ISEC), Bangalore, India, 22-24 February 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3641399.3641446
2024
Conference Publication
The Benefits of Non-Fungible Token (NFT) Technology in Music Copyright
Dong, Jie, Dong, Naipeng and Bai, Guangdong (2024). The Benefits of Non-Fungible Token (NFT) Technology in Music Copyright. 7th International Symposium on Distributed Ledger Technology SDLT 2023, Brisbane, QLD Australia, 30 November – 1 December 2023. Singapore: Springer. doi: 10.1007/978-981-97-0006-6_7
2024
Journal Article
ReLU hull approximation
Ma, Zhongkui, Li, Jiaying and Bai, Guangdong (2024). ReLU hull approximation. Proceedings of the ACM on Programming Languages, 8 (POPL) ARTN 75, 2260-2287. doi: 10.1145/3632917
2024
Journal Article
Effective and Robust Adversarial Training Against Data and Label Corruptions
Zhang, Peng-Fei, Huang, Zi, Xu, Xin-Shun and Bai, Guangdong (2024). Effective and Robust Adversarial Training Against Data and Label Corruptions. IEEE Transactions on Multimedia, 26, 1-12. doi: 10.1109/tmm.2024.3394677
2024
Book
Distributed Ledger Technology: 7th International Symposium, SDLT 2023, Brisbane, QLD, Australia, November 30 – December 1, 2023, Revised Selected Papers
Naipeng Dong, Babu Pillai, Guangdong Bai and Mark Utting eds. (2024). Distributed Ledger Technology: 7th International Symposium, SDLT 2023, Brisbane, QLD, Australia, November 30 – December 1, 2023, Revised Selected Papers. Communications in Computer and Information Science, Heidelberg, Germany: Springer. doi: 10.1007/978-981-97-0006-6
Funding
Current funding
Past funding
Supervision
Availability
- Associate Professor Guangdong Bai is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Supervision history
Current supervision
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Doctor Philosophy
UQIDAR00265: Security Analytics of Internet of Things (IoT)
Principal Advisor
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Doctor Philosophy
Unified Cyber Security Framework for Distributed Learning
Principal Advisor
Other advisors: Professor Ryan Ko
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Doctor Philosophy
Analysing Internet of Thing Applications with Big Data Technique
Principal Advisor
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Doctor Philosophy
Nudge4Cyber: Framework for Designing Accessible and Effective Cyber Security Nudges
Principal Advisor
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Doctor Philosophy
Robustness Verification of Neural Network
Principal Advisor
Other advisors: Dr Naipeng Dong
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Doctor Philosophy
Security of Internet of Things (IoT) Integration
Principal Advisor
Other advisors: Professor Ryan Ko
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Doctor Philosophy
Automation of cyber software security targeting on software and mobile analysis
Principal Advisor
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Doctor Philosophy
IoT security analytics
Principal Advisor
Other advisors: Professor Ryan Ko, Dr Naipeng Dong
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Doctor Philosophy
Privacy attacks and defences in cross-cyber physical domains
Principal Advisor
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Doctor Philosophy
Auditing Privacy Policy Compliance of IoT Applications
Principal Advisor
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Doctor Philosophy
Multimodal Membership Inference: A Causal Perspective
Principal Advisor
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Doctor Philosophy
Distributed data collection infrastructure for IT and OT networks for automated early warning detection
Associate Advisor
Other advisors: Dr Naipeng Dong, Professor Ryan Ko
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Doctor Philosophy
Distributed data collection infrastructure for IT and OT networks for automated early warning detection
Associate Advisor
Other advisors: Dr Naipeng Dong, Professor Ryan Ko
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Doctor Philosophy
Secure, Accountable and Provenance-Centric File System
Associate Advisor
Other advisors: Professor Ryan Ko
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Doctor Philosophy
AI based intrusion detection and response system
Associate Advisor
Other advisors: Associate Professor Dan Kim
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Doctor Philosophy
Adversarial AI Attacks and Defenses in Intrusion Detection System for IoT
Associate Advisor
Other advisors: Associate Professor Dan Kim
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Doctor Philosophy
Automated Penetration Testing using Advanced AI Techniques
Associate Advisor
Other advisors: Associate Professor Dan Kim
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Doctor Philosophy
Fairness in Graph Representation Learning Models
Associate Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Towards Privacy-Preserving and Fairness-Aware Federated Recommendation Systems
Associate Advisor
Other advisors: Dr Ruihong Qiu, Professor Helen Huang
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Doctor Philosophy
Continuous Code Analysis for Rapidly Evolving Software
Associate Advisor
Other advisors: Associate Professor Mark Utting, Dr Guowei Yang
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Doctor Philosophy
Analysis of Machine Learning Systems
Associate Advisor
Other advisors: Dr Naipeng Dong
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Doctor Philosophy
Adversarial AI Attacks and Defenses in Intrusion Detection System for IoT
Associate Advisor
Other advisors: Associate Professor Dan Kim
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Doctor Philosophy
Adaptive, secure and resilient programmable logic controllers (PLCs) and data transfer protocols
Associate Advisor
Other advisors: Professor Tapan Saha, Professor Ryan Ko
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Doctor Philosophy
A Distributed Data Collection Infrastructure For Automating Industrial Control Systems Security
Associate Advisor
Other advisors: Dr Naipeng Dong, Professor Ryan Ko
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Doctor Philosophy
A comprehensive framework for automated cybersecurity assessment, mitigation, and education using graphical security models
Associate Advisor
Other advisors: Associate Professor Dan Kim
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Doctor Philosophy
Exploring the Trustworthiness of Information Retrieval in the Era of Large Language Models
Associate Advisor
Other advisors: Dr Ruihong Qiu, Professor Helen Huang
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Doctor Philosophy
Developing inclusive and culturally sensitive design guidelines for AI-enabled smart homes for people with disabilities in developing countries, based on local needs, preferences, and values
Associate Advisor
Other advisors: Dr Dhaval Vyas
Completed supervision
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2024
Doctor Philosophy
Security Modelling and Analysis of Internet of Things against Evolving Attacks
Associate Advisor
Other advisors: Associate Professor Dan Kim
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2021
Doctor Philosophy
Privacy-preserving Sharing for Genome-wide Analysis
Associate Advisor
Other advisors: Professor Ryan Ko, Dr Caitlin Curtis, Professor Xue Li
Media
Enquiries
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