A Study on Improving M2M Network Security through Abnormal Traffic Control

Abstract

Machine-to-machine (M2M) intelligent network devices are exposed to vulnerable networks and security threats always exist. The devices are composed of low-capacity hardware by their nature and are exposed to various security threats such as worms, viruses and distributed denial of service (DDoS) flooding attacks due to lack of security or antivirus programs installed in the personal computer environment. In this paper, we proposed a network filter that improves the security of M2M intelligent networks by configuring the network security filter in a specific form that can be adapted to M2M intelligent networks. The proposed filter increases user convenience and decreases unnecessary loss. Experimental results show that when the security filter is applied, the response speed of the device improved by more than 50% in an abnormal traffic environment with a cost of less than 10% delay, depending upon the characteristics of the device.