2 citations · 2 across the 1 of their papers we have counts for
7 papers
Label Shift Estimation With Incremental Prior Update
Yunrui Zhang, Gustavo Batista, Salil S. Kanhere
An assumption often made in supervised learning is that the training and testing sets have the same label distribution. However, in real-life scenarios, this assumption rarely hold…
Generalizable IoT Traffic Representations for Cross-Network Device Identification
Arunan Sivanathan, David Warren, Deepak Mishra +8
Machine learning models have demonstrated strong performance in classifying network traffic and identifying Internet-of-Things (IoT) devices, enabling operators to discover and man…
Nosy Layers, Noisy Fixes: Tackling DRAs in Federated Learning Systems using Explainable AI
Meghali Nandi, Arash Shaghaghi, Nazatul Haque Sultan +3
Federated Learning (FL) has emerged as a powerful paradigm for collaborative model training while keeping client data decentralized and private. However, it is vulnerable to Data R…
Revisit Time Series Classification Benchmark: The Impact of Temporal Information for Classification
Yunrui Zhang, Gustavo Batista, Salil S. Kanhere
Time series classification is usually regarded as a distinct task from tabular data classification due to the importance of temporal information. However, in this paper, by perform…
Predicting IoT Device Vulnerability Fix Times with Survival and Failure Time Models
Carlos A Rivera A, Xinzhang Chen, Arash Shaghaghi +2
The rapid integration of Internet of Things (IoT) devices into enterprise environments presents significant security challenges. Many IoT devices are released to the market with mi…
Towards Weaknesses and Attack Patterns Prediction for IoT Devices
Carlos A. Rivera A., Arash Shaghaghi, Gustavo Batista +1
As the adoption of Internet of Things (IoT) devices continues to rise in enterprise environments, the need for effective and efficient security measures becomes increasingly critic…