44 citations · 256 across the 65 of their papers we have counts for
4 papers · 1 filter
Decamouflage: A Framework to Detect Image-Scaling Attacks on Convolutional Neural Networks
Bedeuro Kim, Alsharif Abuadbba, Yansong Gao +4
As an essential processing step in computer vision applications, image resizing or scaling, more specifically downsampling, has to be applied before feeding a normally large image…
Evaluation of Federated Learning in Phishing Email Detection
Chandra Thapa, Jun Wen Tang, Alsharif Abuadbba +5
The use of Artificial Intelligence (AI) to detect phishing emails is primarily dependent on large-scale centralized datasets, which opens it up to a myriad of privacy, trust, and l…
Adversarial Defense by Latent Style Transformations
Shuo Wang, Surya Nepal, Alsharif Abuadbba +2
Machine learning models have demonstrated vulnerability to adversarial attacks, more specifically misclassification of adversarial examples. In this paper, we investigate an attack…
Reliability and Robustness analysis of Machine Learning based Phishing URL Detectors
Bushra Sabir, M. Ali Babar, Raj Gaire +1
ML-based Phishing URL (MLPU) detectors serve as the first level of defence to protect users and organisations from being victims of phishing attacks. Lately, few studies have launc…