Xiaogang Zhu

Orcid: 0000-0002-0647-4747

Affiliations:
  • Swinburne University of Technology, Department of Computer Science and Software Engineering, Melbourne, VIC, Australia


According to our database1, Xiaogang Zhu authored at least 17 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
How COVID-19 impacts telehealth: an empirical study of telehealth services, users and the use of metaverse.
Connect. Sci., 2024

2023
Detecting Vulnerability on IoT Device Firmware: A Survey.
IEEE CAA J. Autom. Sinica, 2023

SHAPFUZZ: Efficient Fuzzing via Shapley-Guided Byte Selection.
CoRR, 2023

On the security of fully homomorphic encryption for data privacy in Internet of Things.
Concurr. Comput. Pract. Exp., 2023

Detecting Union Type Confusion in Component Object Model.
Proceedings of the 32nd USENIX Security Symposium, 2023

2022
Fuzzing: A Survey for Roadmap.
ACM Comput. Surv., January, 2022

Vulnerability Detection in SIoT Applications: A Fuzzing Method on their Binaries.
IEEE Trans. Netw. Sci. Eng., 2022

CSI-Fuzz: Full-Speed Edge Tracing Using Coverage Sensitive Instrumentation.
IEEE Trans. Dependable Secur. Comput., 2022

Path Transitions Tell More: Optimizing Fuzzing Schedules via Runtime Program States.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

2021
Synthesized Corpora to Evaluate Fuzzing for Green Internet of Things Programs.
IEEE Trans. Green Commun. Netw., 2021

Fuzzing With Optimized Grammar-Aware Mutation Strategies.
IEEE Access, 2021

Regression Greybox Fuzzing.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Snipuzz: Black-box Fuzzing of IoT Firmware via Message Snippet Inference.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020
DeFuzz: Deep Learning Guided Directed Fuzzing.
CoRR, 2020

SpeedNeuzz: Speed Up Neural Program Approximation with Neighbor Edge Knowledge.
Proceedings of the 19th IEEE International Conference on Trust, 2020

2019
Bug Searching in Smart Contract.
CoRR, 2019

A Feature-Oriented Corpus for Understanding, Evaluating and Improving Fuzz Testing.
Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security, 2019


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