research
∙
07/03/2023
Interpretability and Transparency-Driven Detection and Transformation of Textual Adversarial Examples (IT-DT)
Transformer-based text classifiers like BERT, Roberta, T5, and GPT-3 hav...
share
research
∙
03/21/2022
Integrity Fingerprinting of DNN with Double Black-box Design and Verification
Cloud-enabled Machine Learning as a Service (MLaaS) has shown enormous p...
research
∙
04/08/2021
Can Differential Privacy Practically Protect Collaborative Deep Learning Inference for the Internet of Things?
Collaborative inference has recently emerged as an intriguing framework ...
research
∙
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...
research
∙
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...
research
∙
06/16/2020
DeepCapture: Image Spam Detection Using Deep Learning and Data Augmentation
Image spam emails are often used to evade text-based spam filters that d...
research
∙
06/05/2020
Can the Multi-Incoming Smart Meter Compressed Streams be Re-Compressed?
Smart meters have currently attracted attention because of their high ef...
research
∙
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...
research
∙
03/16/2020
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
A new collaborative learning, called split learning, was recently introd...
research
∙
11/01/2019
