Changting Lin

Orcid: 0000-0002-8918-6299

According to our database1, Changting Lin authored at least 14 papers between 2018 and 2024.

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

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
Towards understanding bogus traffic service in online social networks.
Frontiers Inf. Technol. Electron. Eng., March, 2024

A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective.
CoRR, 2024

2023
Fraud-Agents Detection in Online Microfinance: A Large-Scale Empirical Study.
IEEE Trans. Dependable Secur. Comput., 2023

iQuery: A Trustworthy and Scalable Blockchain Analytics Platform.
IEEE Trans. Dependable Secur. Comput., 2023

One4All: Manipulate one agent to poison the cooperative multi-agent reinforcement learning.
Comput. Secur., 2023

Adversarial Attacks on Skeleton-Based Sign Language Recognition.
Proceedings of the Intelligent Robotics and Applications - 16th International Conference, 2023

2022
A Large-Scale Empirical Study on the Vulnerability of Deployed IoT Devices.
IEEE Trans. Dependable Secur. Comput., 2022

A Secure and Authenticated Mobile Payment Protocol Against Off-Site Attack Strategy.
IEEE Trans. Dependable Secur. Comput., 2022

One Bad Apple Spoils the Barrel: Understanding the Security Risks Introduced by Third-Party Components in IoT Firmware.
CoRR, 2022

A large-scale empirical analysis of the vulnerabilities introduced by third-party components in IoT firmware.
Proceedings of the ISSTA '22: 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, South Korea, July 18, 2022

2021
Multi-level Alignment Network for Domain Adaptive Cross-modal Retrieval.
Neurocomputing, 2021

MPInspector: A Systematic and Automatic Approach for Evaluating the Security of IoT Messaging Protocols.
Proceedings of the 30th USENIX Security Symposium, 2021

2020
Rapido: Scaling blockchain with multi-path payment channels.
Neurocomputing, 2020

2018
Learning to Classify Blockchain Peers According to Their Behavior Sequences.
IEEE Access, 2018


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