Taxonomy of Intrusion Detection and Its Effectiveness in Internet of Things

Intrusion detection systems (IDSs) provide defense against cyberattacks in distributed systems. In this chapter, the research studies related to intruder detection technique in IoT are analyzed for privacy and efficiency. Intrusion detections are classified into two categories: (1) Anomaly detection and (2) signature detection. The specification detection method belongs to anomaly detection based on a rule-generating technique. This study shows that anomaly detection technique has notable privacy features compared to the signature technique. The random forest rule generation method offers high privacy and is more efficient in IDS. IoT devices are usually resource-constrained devices and thus require lightweight methods for privacy protection. The feature selection method such as the weighted cuckoo search algorithm has a higher detection value in the IDS.