Dec 18, 2018 · IoTguard uses semi-supervised learning to distinguish between malicious and benign device behaviours using the network traffic generated by ...

IoTguard uses semi-supervised learning to distinguish between malicious and benign device behaviours using the network traffic generated by devices. In order to ...

The results show that IoTguard achieves high accuracy, in differentiating various types of malicious and benign traffic, with low false positive rates, ...

The growing popularity of Internet-of-Things (IoT) has created the need for network-based traffic anomaly detection systems that could identify misbehaving ...

NDR captures mirrored traffic from the network switch to identify the connected devices and detects abnormal traffic patterns from their behaviors. One method ...

Real-time IoT Device Activity Detection in Edge Networks. In Proceedings of the 12th International Conference on Network and System Security (NSS '18).

Dec 18, 2024 · Discover how IoT and Edge AI are transforming industries with real-time analytics, enabling faster decisions, smarter operations, ...

TL;DR: The results show that IoTguard achieves high accuracy, in differentiating various types of malicious and benign traffic, with low false positive ...

This paper presents VegaEdge, an AI framework optimized for edge-IoT devices capable of real-time vehicle detection and tracking, trajectory forecasting, and ...

Aug 27, 2024 · Edge computing is a technology that processes data near its source, like a local device or nearby server, instead of sending it to a central data center.