Ahmed Imteaj

Assistant Professor

Southern Illinois University Carbondale

United States

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Ahmed Imteaj is an Assistant Professor at Southern Illinois University Carbondale, United States. His research areas primarily focus on blockchain technology, federated learning, cybersecurity, and machine learning. Recent publications include works on cyber-secure federated learning, the sustainability of adversarial training, and securing user privacy in cloud-based services.

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Collaborators (4)

M. Hadi Amini

Assistant Professor

Florida International University

UNITED STATES

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Jian Li

State University of New York

UNITED STATES

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Arif Mohaimin Sadri

Assistant Professor

University of Oklahoma

UNITED STATES

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Abdur Rahman Bin Shahid

Assistant Professor

Southern Illinois University Carbondale

UNITED STATES

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Ahmed Imteaj

Research Interests

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Articles (18)

Evaluating Sustainability and Social Costs of Adversarial Training in Machine Learning

Sticks and stones may break my bones, but words will never hurt me!—Navigating the cybersecurity risks of generative AI

Blockchain-Empowered Cyber-Secure Federated Learning for Trustworthy Edge Computing

Blockchain-Empowered Cyber-Secure Federated Learning for Trustworthy Edge Computing

Securing User Privacy in Cloud-Based Whiteboard Services Against Health Attribute Inference Attacks

Securing User Privacy in Cloud-Based Whiteboard Services Against Health Attribute Inference Attacks

FedAVO: Improving Communication Efficiency in Federated Learning with African Vultures Optimizer

A Novel Scalable Reconfiguration Model for the Postdisaster Network Connectivity of Resilient Power Distribution Systems

A Survey on Secure and Private Federated Learning Using Blockchain: Theory and Application in Resource-constrained Computing

Leveraging Blockchain Interoperability for Interdependent Networks

Assessing Wearable Human Activity Recognition Systems Against Data Poisoning Attacks in Differentially-Private Federated Learning

Leveraging asynchronous federated learning to predict customers financial distress

Examining Mental Disorder/Psychological Chaos through Various ML and DL Techniques: A Critical Review

A Survey on Federated Learning for Resource-Constrained IoT Devices

FedResilience: A Federated Learning Application to Improve Resilience of Resource-Constrained Critical Infrastructures

Data analytics to evaluate the impact of infectious disease on economy: Case study of COVID-19 pandemic

FedPARL: Client Activity and Resource-Oriented Lightweight Federated Learning Model for Resource-Constrained Heterogeneous IoT Environment

A Survey on Federated Learning for Resource-Constrained IoT Devices

Collaborators (4)

M. Hadi Amini

Jian Li

Arif Mohaimin Sadri

Abdur Rahman Bin Shahid

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