Iqbal Gondal

Associate Dean/Prof Cloud, Systems and Security

RMIT University

Australia

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Iqbal Gondal is an Associate Dean and Professor of Cloud, Systems, and Security at RMIT University in Australia. His research encompasses areas such as AI-blockchain integration, cybersecurity, federated learning, and IoT security, as evidenced by his recent publications. His work includes the development of frameworks for secure communication in connected environments and proactive defense mechanisms to enhance cybersecurity. He is actively contributing to the advancement of technology in contemporary digital systems.

Iqbal Gondal

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Articles (21)

Fed-DTB: A Dynamic Trust-Based Framework for Secure and Efficient Federated Learning in IoV Networks: Securing V2V/V2I Communication

AI-Blockchain Integration for Real-Time Cybersecurity: System Design and Evaluation

Cross-Domain Fake News Detection Through Fusion of Evidence from Multiple Social Media Platforms

Proactive defense mechanism: Enhancing IoT security through diversity-based moving target defense and cyber deception

Smart Contract-Based Access Control Framework for Internet of Things Devices

Multiagent Information Fusion for Connected Driving: A Review

False Data Detection in a Clustered Smart Grid Using Unscented Kalman Filter

Sensitivity Analysis for Vulnerability Mitigation in Hybrid Networks

A framework for data privacy and security accountability in data breach communications

A Survey on the Adoption of Blockchain in IoT: Challenges and Solutions

A Smart Priority-Based Traffic Control System for Emergency Vehicles

Cross-compiler bipartite vulnerability search

Malware detection in edge devices with fuzzy oversampling and dynamic class weighting

Rapid health data repository allocation using predictive machine learning

Cyberattack triage using incremental clustering for intrusion detection systems

Function similarity using family context

Guest Editorial Special Issue on Privacy and Security in Distributed Edge Computing and Evolving IoT

Guest Editorial: Security, Reliability, Privacy, and Quality in Industrial Automation and Control

Hybrid intrusion detection system based on the stacking ensemble of C5 decision tree classifier and one class support vector machine

Robust Malware Defense in Industrial IoT Applications Using Machine Learning with Selective Adversarial Samples

Vulnerability Modelling for Hybrid Industrial Control System Networks

Collaborators (11)

Alireza Bab-Hadiashar

Andrew Stranieri

Reza Hoseinnezhad

Sona Taheri

Sardar M. N. Islam

Taiwo Oseni

Abdullahi Chowdhury

Ammar Alazab

Mark Gregory

Syed Islam

Joarder Kamruzzaman

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