Home networks increasingly support important networked applications with limited
professional network administration support, while sophisticated attacks pose enormous …

Abstract Graph Neural Networks (GNNs) have garnered intensive attention for Network
Intrusion Detection System (NIDS) due to their suitability for representing the network traffic …

Smart homes, powered by the Internet of Things, offer great convenience but also pose
security concerns due to abnormal behaviors, such as improper operations of users and …

In the Internet of Things (IoT) scenario, the device diversity and data sparsity present a
significant challenge for malicious traffic detection, notably the “small sample problem” …

Along with the increasing popularity of smart home IoT devices, more users are turning to
smart home automation platforms to control and automate their IoT devices. However, IoT …

Container security has received much research attention recently. Previous work has
proposed to apply various machine learning techniques to detect security attacks in …

Malware has been a real threat to Internet of Things (IoT). Although commercial antivirus
solutions can detect malware files and provide label information indicating malware types or …

With the advancement of IoT technology, smart IoT systems have become integral to
industrial production and daily life. However, they face significant security and privacy …

Anomaly-based intrusion detection systems are tasked with identifying deviations from
established benign network behaviors, assuming such deviations to be indicators of …

Abstract Internet of Things (IoT) devices have increased drastically in complexity and
prevalence within the last decade. Alongside the proliferation of IoT devices and …