A Transformer-Based Framework for Payload Malware Detection and Classification

arXiv:2403.18223v1 Announce Type: cross
Abstract: As malicious cyber threats become more sophisticated in breaching computer networks, the need for effective intrusion detection systems (IDSs) becomes crucial. Techniques such as Deep Packet Inspection (DPI) have been introduced to allow IDSs analyze the content of network packets, providing more context for identifying potential threats. IDSs traditionally rely on using anomaly-based and signature-based detection techniques to detect unrecognized and suspicious activity. Deep learning techniques have shown great potential in DPI for IDSs due …

abstract analyze arxiv become classification computer context cs.ai cs.cr cs.lg cyber detection framework idss malware malware detection network networks systems threats transformer type