39 citations · 58 across the 21 of their papers we have counts for
4 papers · 1 filter
DeepCapture: Image Spam Detection Using Deep Learning and Data Augmentation
Bedeuro Kim, Sharif Abuadbba, Hyoungshick Kim
Image spam emails are often used to evade text-based spam filters that detect spam emails with their frequently used keywords. In this paper, we propose a new image spam email dete…
Can the Multi-Incoming Smart Meter Compressed Streams be Re-Compressed?
Sharif Abuadbba, Ayman Ibaida, Ibrahim Khalil +3
Smart meters have currently attracted attention because of their high efficiency and throughput performance. They transmit a massive volume of continuously collected waveform readi…
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
Sharif Abuadbba, Kyuyeon Kim, Minki Kim +5
A new collaborative learning, called split learning, was recently introduced, aiming to protect user data privacy without revealing raw input data to a server. It collaboratively r…
End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
Yansong Gao, Minki Kim, Sharif Abuadbba +6
This work is the first attempt to evaluate and compare felderated learning (FL) and split neural networks (SplitNN) in real-world IoT settings in terms of learning performance and…