Improving security in IoT-based human activity recognition: a correlation-based anomaly detection approach

• المؤلفون الرئيسيون: Fan, Jiani, Liu, Ziyao, Du, Hongyang, Kang, Jiawen, Niyato, Dusit, Lam, Kwok-Yan
• مؤلفون آخرون: College of Computing and Data Science
• التنسيق: مقال
• اللغة: English
• منشور في: 2025
• الموضوعات: Computer and Information Science; Human activity recognition; Anomaly detection; Monitoring; Internet of Things; Data models; Context modelling; Correlation; Security; Accuracy; Predictive models
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/182538

Anomaly detection in Human Activity Recognition (HAR) is a critical subfield that leverages data from the Internet of Things (IoT) to monitor human activities and detect errors or abnormal events. Conventional rule-based approaches often fail to capture the intricate relationships between sensor val...