Evaluation of Low-cost Operation of a Malware Detection Mechanism using Processor Information Targeting the IoT

In recent years, the demand for IoT devices has increased dramatically, and they are used in a variety of places, such as sensors, in-vehicle terminals, control devices in factories, and medical equipment in hospitals. Furthermore, attackers are also increasingly targeting IoT devices, making it necessary to implement security countermeasures. However, IoT devices rarely have sufficient resources like high-end products such as PCs and servers. Therefore, we are developing a system that can detect malware with lower resources. In this paper we measured the classification accuracy of the detection mechanism using random forests and reduce the circuit scale and power consumption, targeting the RISCV architecture. As a result, we show that the detection mechanism can be made more accurate in classifying normal programs and malware, and the detection mechanism can be made lower cost.