Securing IoT: Unveiling Attacks With Multiview-Multitask Learning

This paper presents M²VT, a new AI defense system that uses multiview-multitask learning (processing multiple sets of features at once to perform several related tasks) to detect and classify cyberattacks on IoT devices (connected smart devices and systems). The system achieves over 96% accuracy by using autoencoders (neural networks that compress and extract important patterns from data) and LSTM networks (a type of AI that understands sequences over time) to simultaneously detect attacks, categorize them, and classify their types.