4 papers
Binary Anomaly Detection in Streaming IoT Traffic under Concept Drift
Rodrigo Matos Carnier, Laura Lahesoo, Kensuke Fukuda
With the growing volume of Internet of Things (IoT) network traffic, machine learning (ML)-based anomaly detection is more relevant than ever. Traditional batch learning models fac…
GothX: a generator of customizable, legitimate and malicious IoT network traffic
Manuel Poisson, Rodrigo Carnier, Kensuke Fukuda
In recent years, machine learning-based anomaly detection (AD) has become an important measure against security threats from Internet of Things (IoT) networks. Machine learning (ML…
A hybrid approach for dynamically training a torque prediction model for devising a human-machine interface control strategy
Sharmita Dey, Takashi Yoshida, Robert H. Foerster +4
Human-machine interfaces (HMI) play a pivotal role in the rehabilitation and daily assistance of lower-limb amputees. The brain of such interfaces is a control model that detects t…
Comparison Between IPv4 to IPv6 Transition Techniques
Edwin Cordeiro, Rodrigo Carnier, Wagner L Zucchi
The IPv4 addresses exhaustion demands a protocol transition from IPv4 to IPv6. The original transition technique, the dual stack, is not widely deployed yet and it demanded the cre…