A5036190937- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Adversarial Robustness in Machine Learning
- Brain Tumor Detection and Classification
- Advanced Data and IoT Technologies
- IoT and Edge/Fog Computing
- Internet Traffic Analysis and Secure E-voting
- Advanced Neural Network Applications
- Traffic Prediction and Management Techniques
- Data Mining Algorithms and Applications
- Recommender Systems and Techniques
- Stochastic Gradient Optimization Techniques
- Advanced Computing and Algorithms
- Rough Sets and Fuzzy Logic
- Cloud Computing and Resource Management
Hunan University
2023-2024
Abstract Distributed computing frameworks play a crucial role in supporting compute-intensive applications the era of big data. The growing demand for resources has spurred interconnection data centers, leading to formation supercomputing Internet. MapReduce is popular distributed framework designed large independent clusters. original deployed on Internet performs inefficiently due redundant geo-distributed reduce operations. Nonetheless, its abstraction remains significant potential. This...
As a novel distributed machine learning scheme, federated (FL) efficiently realizes the collaborative training of models by global participants while also protecting their data privacy. Due to independence participants' local and inability FL server access data, many IIoT applications with strong sensitivity are increasingly incorporating technology. However, it exposes great security vulnerability. Malicious adversaries manipulate perform covert targeted poisoning attacks or other harmful...