An Anomaly Behavior based Detection and Prevention of DoS Attack in IoT Environment

IoT is a predominant technology for the information gathering and sharing for various applications. In IoT, the devices are communicated using IEEE 802.11 and IEEE 802.15.4. Low Power IEEE 802.11 is used as communication protocol for IoT nodes to achieve the higher bandwidth and good coverage range. The MAC Layer protocols are more vulnerable to Denial of Service (DoS) attacks such as de-authentication attack, disassociation attack, injection test, and authentication flood and association flood. IoT environment is necessary to monitor to detect attacks and need to prevent them for incessant services. In this paper, Topology Management Method (TMM) is proposed to prevent the DoS attacks based on behavior analysis. In this approach, the sequence of protocol transitions at MAC layer is interrogated over a period of time. The transitions are monitored and used to check the behavior of the IoT node communications. In addition, Fine grained detection algorithm used to detect the wireless node anomalies at the MAC layer. These techniques provide an efficient detection and prevention in IoT environment.