5 papers
Rethinking IoT Intrusion Detection: Augmenting Routing Metrics with Radio Features
Yichang Sun, Andreas Johnsson, Sourasekhar Banerjee
Machine learning-based intrusion detection systems (IDS) for RPL-based IoT networks often rely solely on routing layer features, which provide only a partial view of network behavi…
Towards Intrusion Detection Systems for RPL-based IoT Networks using Foundation Models
Elias Lunderbye, Sourasekhar Banerjee, Christian Rohner +1
AI-based intrusion detection systems (IDS) have shown promise in detecting attacks on IoT systems. In this work, we explore the use of foundation models to detect and identify atta…
Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems
Sourasekhar Banerjee, David Bergqvist, Salman Toor +2
Distribution shifts in attack patterns within RPL-based IoT networks pose a critical threat to the reliability and security of large-scale connected systems. Intrusion Detection Sy…
Federated Frank-Wolfe Algorithm
Ali Dadras, Sourasekhar Banerjee, Karthik Prakhya +1
Federated learning (FL) has gained a lot of attention in recent years for building privacy-preserving collaborative learning systems. However, FL algorithms for constrained machine…
Personalized Multi-tier Federated Learning
Sourasekhar Banerjee, Ali Dadras, Alp Yurtsever +1
The key challenge of personalized federated learning (PerFL) is to capture the statistical heterogeneity properties of data with inexpensive communications and gain customized perf…