activity
20222024
most citedExplainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research

435 citations · 554 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2024

Reputation-Based Federated Learning Defense to Mitigate Threats in EEG Signal Classification

Zhibo Zhang, Pengfei Li, Ahmed Y. Al Hammadi +3

This paper presents a reputation-based threat mitigation framework that defends potential security threats in electroencephalogram (EEG) signal classification during model aggregat…

cs.CR2024

A Robust Adversary Detection-Deactivation Method for Metaverse-oriented Collaborative Deep Learning

Pengfei Li, Zhibo Zhang, Ameena S. Al-Sumaiti +2

Metaverse is trending to create a digital circumstance that can transfer the real world to an online platform supported by large quantities of real-time interactions. Pre-trained A…

eess.SP20231 cited

Data Poisoning Attacks on EEG Signal-based Risk Assessment Systems

Zhibo Zhang, Sani Umar, Ahmed Y. Al Hammadi +3

Industrial insider risk assessment using electroencephalogram (EEG) signals has consistently attracted a lot of research attention. However, EEG signal-based risk assessment system…

cs.LG20231 cited

Explainable Label-flipping Attacks on Human Emotion Assessment System

Zhibo Zhang, Ahmed Y. Al Hammadi, Ernesto Damiani +1

This paper's main goal is to provide an attacker's point of view on data poisoning assaults that use label-flipping during the training phase of systems that use electroencephalogr…

eess.SY202394 cited

Multi Feature Data Fusion-Based Load Forecasting of Electric Vehicle Charging Stations Using a Deep Learning Model

Prince Aduama, Zhibo Zhang, Ameena S. Al Sumaiti

We propose a forecasting technique based on multi-feature data fusion to enhance the accuracy of an electric vehicle (EV) charging station load forecasting deep-learning model. The…

cs.LG202323 cited

Explainable Data Poison Attacks on Human Emotion Evaluation Systems based on EEG Signals

Zhibo Zhang, Sani Umar, Ahmed Y. Al Hammadi +5

The major aim of this paper is to explain the data poisoning attacks using label-flipping during the training stage of the electroencephalogram (EEG) signal-based human emotion eva…