Dehghantanha, Ali

A survey on security and privacy of federated learning

Mothukuri, V., Parizi, R. M., Pouriyeh, S., Huang, Y., Dehghantanha, A., & Srivastava, G. (2021) · Future Generation Computer Systems

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 1,480

Internet of Things security and forensics: Challenges and opportunities

Conti, M., Dehghantanha, A., Franke, K., & Watson, S. (2018) · Future Generation Computer Systems

Digital and Cyber ForensicsIoT and Edge/Fog Computing

Cited by 720

A robust privacy-preserving federated learning model against model poisoning attacks

Yazdinejad, A., Dehghantanha, A., Karimipour, H., Srivastava, G., & Parizi, R. M. (2024) · IEEE Transactions on Information Forensics and Security

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 380

Sidechain technologies in blockchain networks: an examination and state-of-the-art review

Singh, A., Click, K., Parizi, R. M., Zhang, Q., Dehghantanha, A., & Choo, K.-K. R. (2020) · Journal of Network and Computer Applications

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 360

Industrial Big Data Analytics: Challenges and Opportunities

Al-Abassi, A., Karimipour, H., HaddadPajouh, H., Dehghantanha, A., & Parizi, R. M. (2020) · Handbook of Big Data Privacy

Digital Transformation in IndustryImpact of AI and Big Data on Business and Society

Cited by 32

SoK: The Attack Surface of Agentic AI - Tools and Autonomy

Dehghantanha, A., & Homayoun, S. (2026) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 0