166 citations · 274 across the 9 of their papers we have counts for
9 papers
A Study on Semi-Supervised Detection of DDoS Attacks under Class Imbalance
Ehsan Hallaji, Vaishnavi Shanmugam, Roozbeh Razavi-Far +1
One of the most difficult challenges in cybersecurity is eliminating Distributed Denial of Service (DDoS) attacks. Automating this task using artificial intelligence is a complex p…
FedNIA: Noise-Induced Activation Analysis for Mitigating Data Poisoning in Federated Learning
Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif
Federated learning systems are increasingly threatened by data poisoning attacks, where malicious clients compromise global models by contributing tampered updates. Existing defens…
A Study on the Importance of Features in Detecting Advanced Persistent Threats Using Machine Learning
Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif
Advanced Persistent Threats (APTs) pose a significant security risk to organizations and industries. These attacks often lead to severe data breaches and compromise the system for…
TrustChain: A Blockchain Framework for Auditing and Verifying Aggregators in Decentralized Federated Learning
Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif
The server-less nature of Decentralized Federated Learning (DFL) requires allocating the aggregation role to specific participants in each federated round. Current DFL architecture…
Federated Continual Learning: Concepts, Challenges, and Solutions
Parisa Hamedi, Roozbeh Razavi-Far, Ehsan Hallaji
Federated Continual Learning (FCL) has emerged as a robust solution for collaborative model training in dynamic environments, where data samples are continuously generated and dist…
Decentralized Federated Learning: A Survey on Security and Privacy
Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif +2
Federated learning has been rapidly evolving and gaining popularity in recent years due to its privacy-preserving features, among other advantages. Nevertheless, the exchange of mo…
Learning From High-Dimensional Cyber-Physical Data Streams for Diagnosing Faults in Smart Grids
Hossein Hassani, Ehsan Hallaji, Roozbeh Razavi-Far +1
The performance of fault diagnosis systems is highly affected by data quality in cyber-physical power systems. These systems generate massive amounts of data that overburden the sy…
A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems
Ehsan Hallaji, Roozbeh Razavi-Far, Meng Wang +2
This paper presents a novel data-driven framework to aid in system state estimation when the power system is under unobservable false data injection attacks. The proposed framework…
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms
Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif
The advent of federated learning has facilitated large-scale data exchange amongst machine learning models while maintaining privacy. Despite its brief history, federated learning…