Jiale Zhang
Orcid: 0000-0002-2143-5666Affiliations:
- Yangzhou University, School of Information Engineering, Yangzhou, China
- Nanjing University of Aeronautics and Astronautics, School of Computer Science and Technology, China (PhD 2021)
According to our database1,
Jiale Zhang
authored at least 56 papers
between 2018 and 2024.
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Bibliography
2024
Application programming interface recommendation for smart contract using deep learning from augmented code representation.
J. Softw. Evol. Process., August, 2024
Neural Comput. Appl., July, 2024
Ponzi Scheme Detection in Smart Contract via Transaction Semantic Representation Learning.
IEEE Trans. Reliab., June, 2024
IEEE Internet Things J., June, 2024
Fine-grained smart contract vulnerability detection by heterogeneous code feature learning and automated dataset construction.
J. Syst. Softw., March, 2024
FLPurifier: Backdoor Defense in Federated Learning via Decoupled Contrastive Training.
IEEE Trans. Inf. Forensics Secur., 2024
BadCleaner: Defending Backdoor Attacks in Federated Learning via Attention-Based Multi-Teacher Distillation.
IEEE Trans. Dependable Secur. Comput., 2024
CoRR, 2024
CoRR, 2024
A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research.
CoRR, 2024
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
Proceedings of the IEEE International Conference on Communications, 2024
2023
Comput. Secur., September, 2023
Comput. Electr. Eng., September, 2023
Neural Comput. Appl., August, 2023
LAFED: A lightweight authentication mechanism for blockchain-enabled federated learning system.
Future Gener. Comput. Syst., August, 2023
VPFL: A verifiable privacy-preserving federated learning scheme for edge computing systems.
Digit. Commun. Networks, August, 2023
<i>ASSBert</i>: Active and semi-supervised bert for smart contract vulnerability detection.
J. Inf. Secur. Appl., March, 2023
Combine sliced joint graph with graph neural networks for smart contract vulnerability detection.
J. Syst. Softw., 2023
Extended Abstract of Combine Sliced Joint Graph with Graph Neural Networks for Smart Contract Vulnerability Detection.
Proceedings of the IEEE International Conference on Software Analysis, 2023
Proceedings of the Machine Learning for Cyber Security - 5th International Conference, 2023
Proceedings of the Machine Learning for Cyber Security - 5th International Conference, 2023
Proceedings of the Algorithms and Architectures for Parallel Processing, 2023
2022
RobustFL: Robust Federated Learning Against Poisoning Attacks in Industrial IoT Systems.
IEEE Trans. Ind. Informatics, 2022
Empir. Softw. Eng., 2022
Detecting and mitigating poisoning attacks in federated learning using generative adversarial networks.
Concurr. Comput. Pract. Exp., 2022
Cyber situation perception for Internet of Things systems based on zero-day attack activities recognition within advanced persistent threat.
Concurr. Comput. Pract. Exp., 2022
A Blockchain-based Multi-layer Decentralized Framework for Robust Federated Learning.
Proceedings of the International Joint Conference on Neural Networks, 2022
HBMD-FL: Heterogeneous Federated Learning Algorithm Based on Blockchain and Model Distillation.
Proceedings of the Emerging Information Security and Applications, 2022
Edge-based Protection Against Malicious Poisoning for Distributed Federated Learning.
Proceedings of the 25th IEEE International Conference on Computer Supported Cooperative Work in Design, 2022
Proceedings of the Blockchain Technology and Emerging Technologies, 2022
Proceedings of the Web and Big Data - 6th International Joint Conference, 2022
Proceedings of the Applied Cryptography and Network Security Workshops, 2022
2021
Wirel. Commun. Mob. Comput., 2021
Predicting the APT for Cyber Situation Comprehension in 5G-Enabled IoT Scenarios Based on Differentially Private Federated Learning.
Secur. Commun. Networks, 2021
PoisonGAN: Generative Poisoning Attacks Against Federated Learning in Edge Computing Systems.
IEEE Internet Things J., 2021
OAC-HAS: outsourced access control with hidden access structures in fog-enhanced IoT systems.
Connect. Sci., 2021
Defending against Membership Inference Attacks in Federated learning via Adversarial Example.
Proceedings of the 17th International Conference on Mobility, Sensing and Networking, 2021
2020
FedMEC: Improving Efficiency of Differentially Private Federated Learning via Mobile Edge Computing.
Mob. Networks Appl., 2020
LVPDA: A Lightweight and Verifiable Privacy-Preserving Data Aggregation Scheme for Edge-Enabled IoT.
IEEE Internet Things J., 2020
Proceedings of the Security and Privacy in Digital Economy, 2020
Proceedings of the Security, Privacy, and Anonymity in Computation, Communication, and Storage, 2020
Proceedings of the 26th IEEE International Conference on Parallel and Distributed Systems, 2020
Beyond Model-Level Membership Privacy Leakage: an Adversarial Approach in Federated Learning.
Proceedings of the 29th International Conference on Computer Communications and Networks, 2020
Proceedings of the 2020 IEEE International Conference on Communications, 2020
Dynamic Sample Selection for Federated Learning with Heterogeneous Data in Fog Computing.
Proceedings of the 2020 IEEE International Conference on Communications, 2020
Proceedings of the Frontiers in Cyber Security - Third International Conference, 2020
2019
Cyber Situation Comprehension for IoT Systems based on APT Alerts and Logs Correlation.
Sensors, 2019
Proceedings of the 18th IEEE International Conference On Trust, 2019
Correlate the Advanced Persistent Threat Alerts and Logs for Cyber Situation Comprehension.
Proceedings of the Security and Privacy in Social Networks and Big Data, 2019
An Efficient Federated Learning Scheme with Differential Privacy in Mobile Edge Computing.
Proceedings of the Machine Learning and Intelligent Communications, 2019
PDGAN: A Novel Poisoning Defense Method in Federated Learning Using Generative Adversarial Network.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2019
A Privacy-Preserving Access Control Scheme with Verifiable and Outsourcing Capabilities in Fog-Cloud Computing.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2019
Proceedings of the 2019 IEEE Global Communications Conference, 2019
2018
Data Security and Privacy-Preserving in Edge Computing Paradigm: Survey and Open Issues.
IEEE Access, 2018
LPDA-EC: A Lightweight Privacy-Preserving Data Aggregation Scheme for Edge Computing.
Proceedings of the 15th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, 2018