Intrusion detection systems for smart home IoT devices: experimental comparison study

With the growing number of IoT related devices, smart homes promise to make our lives easier and more comfortable. However, the increased deployment of such smart devices brings a lot of security and privacy risks. In order to overcome such risks, Intrusion Detection Systems are presented as pertinent tools that can provide network-level protection for smart devices deployed in home environments. These systems monitor the network activities of the smart home-connected devices and focus on alerting suspicious or malicious activity. They also can deal with detected abnormal activities by hindering the impostors in accessing the victim devices. However, the employment of such systems in the context of smart home can be challenging due to the devices hardware limitations, which may restrict their ability to counter the existing and emerging attack vectors. Therefore, this paper proposes an experimental comparison between the widely used open-source NIDSs namely Snort, Suricata and Bro (currently known as Zeek) to find the most appropriate IDS for smart homes in term of resources consumption including CPU and memory utilisation. Experimental Results show that Suricata and Bro are the best performing NIDS for smart homes.