Ao Liu

Orcid: 0000-0002-8412-6414

Affiliations:
  • Sichuan University, School of Cyber Science and Engineering, Chengdu, China
  • Tianjin University of Technology, Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, China (former)


According to our database1, Ao Liu authored at least 13 papers between 2019 and 2024.

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

Timeline

Legend:

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Bibliography

2024
AN-GCN: An Anonymous Graph Convolutional Network Against Edge-Perturbing Attacks.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

Chaos-Based Index-of-Min Hashing Scheme for Cancellable Biometrics Security.
IEEE Trans. Inf. Forensics Secur., 2024

Towards Inductive Robustness: Distilling and Fostering Wave-Induced Resonance in Transductive GCNs against Graph Adversarial Attacks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
An artificial immunity based intrusion detection system for unknown cyberattacks.
Appl. Soft Comput., November, 2023

Defending Byzantine attacks in ensemble federated learning: A reputation-based phishing approach.
Future Gener. Comput. Syst., 2023

Graph Agent Network: Empowering Nodes with Decentralized Communications Capabilities for Adversarial Resilience.
CoRR, 2023

FedCliP: Federated Learning with Client Pruning.
CoRR, 2023

2021
SFE-GACN: A novel unknown attack detection under insufficient data via intra categories generation in embedding space.
Comput. Secur., 2021

2020
Anonymized GCN: A Novel Robust Graph Embedding Method via Hiding Node Position in Noise.
CoRR, 2020

SFE-GACN: A Novel Unknown Attack Detection Method Using Intra Categories Generation in Embedding Space.
CoRR, 2020

BAGKD: A Batch Authentication and Group Key Distribution Protocol for VANETs.
IEEE Commun. Mag., 2020

2019
An Intrusion Detection System Based on a Quantitative Model of Interaction Mode Between Ports.
IEEE Access, 2019

The Improved Model for Anomaly Detection Based on Clustering and Dividing of Flow.
Proceedings of the Fourth IEEE International Conference on Data Science in Cyberspace, 2019


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