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07/25/2023
Federated Split Learning with Only Positive Labels for resource-constrained IoT environment
Distributed collaborative machine learning (DCML) is a promising method ...
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07/23/2023
ACE: A Consent-Embedded privacy-preserving search on genomic database
In this paper, we introduce ACE, a consent-embedded searchable encryptio...
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07/18/2023
Discretization-based ensemble model for robust learning in IoT
IoT device identification is the process of recognizing and verifying co...
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03/01/2023
Access-based Lightweight Physical Layer Authentication for the Internet of Things Devices
Physical-layer authentication is a popular alternative to the convention...
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02/03/2023
Vertical Federated Learning: Taxonomies, Threats, and Prospects
Federated learning (FL) is the most popular distributed machine learning...
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04/07/2022
Enabling Deep Learning for All-in EDGE paradigm
Deep Learning-based models have been widely investigated, and they have ...
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04/07/2022
Transformer-Based Language Models for Software Vulnerability Detection: Performance, Model's Security and Platforms
The large transformer-based language models demonstrate excellent perfor...
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02/22/2022
Graph Lifelong Learning: A Survey
Graph learning substantially contributes to solving artificial intellige...
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09/19/2021
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance
Federated Learning (FL), Split Learning (SL), and SplitFed Learning (SFL...
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06/09/2021
FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation
An integrated clinical environment (ICE) enables the connection and coor...
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03/03/2021
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of Things
Federated learning (FL) and split learning (SL) are state-of-the-art dis...
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11/25/2020
Advancements of federated learning towards privacy preservation: from federated learning to split learning
In the distributed collaborative machine learning (DCML) paradigm, feder...
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08/24/2020
Precision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy
Precision health leverages information from various sources, including o...
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07/27/2020
FedEmail: Performance Measurement of Privacy-friendly Phishing Detection Enabled by Federated Learning
Artificial intelligence (AI) has been applied in phishing email detectio...
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04/25/2020
SplitFed: When Federated Learning Meets Split Learning
Federated learning (FL) and split learning (SL) are two recent distribut...
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03/30/2020
End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
This work is the first attempt to evaluate and compare felderated learni...
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03/16/2020