A Power-Efficient Approach to Detect Mobile Threats on the Emergent Network Environment

Abstract

Mobile and IoT devices are blooming, and their applications are prevailing worldwide. In the meantime, the Industry 4.0 trend converges industrial control systems with the internet environment, which makes it vulnerable. Mobile and IoT applications provide seamless connectivity to the emergent network environment for daily work. As mobile phones contain privacy information, malicious mobile applications could compromise mobile devices and cause financial losses. Moreover, attackers could launch DDoS attacks to exhaust a resource of mobile or IoT devices in the emergent network environment. Static malware analysis consumes less computing resources and power than dynamic analysis. This study proposes a power-efficient solution to identify mobile threats, which applies taint analysis to protect the emergent network environment. The experimental results show that the proposed approach could detect mobile malware efficiently.

Keywords

• Internet of Things
• malware detection
• static analysis
• cyberattacks