Enhancing IoT Malware Detection through Adaptive Model Parallelism and Resource Optimization

arXiv:2404.08808v1 Announce Type: new
Abstract: The widespread integration of IoT devices has greatly improved connectivity and computational capabilities, facilitating seamless communication across networks. Despite their global deployment, IoT devices are frequently targeted for security breaches due to inherent vulnerabilities. Among these threats, malware poses a significant risk to IoT devices. The lack of built-in security features and limited resources present challenges for implementing effective malware detection techniques on IoT devices. Moreover, existing methods assume access to all device resources for …

arxiv breaches capabilities communication computational connectivity cs.cr cs.dc deployment detection devices global integration iot iot devices iot malware malware malware detection networks optimization resource risk security security breaches threats vulnerabilities