A new IDS for detecting jamming attacks in WBAN

Abstract

Thanks to the Internet of Things (IoT), our life becomes more flexible in various areas, like emergency, transport, building management and healthcare. Our work focus on the health technology named Wireless Body Area Network (WBAN), which consists of mini medical sensors. Those sensors are attached on the human body to collect biomedical parameters and send them to the medical center. However, because of the presence of wireless network the use of those applications are very sensitive to various types of exterior attacks and anomalies, which make the field of security a very big challenge. Jamming attacks are one of the most dangers attacks in WBAN system, which disrupt and block the communication between the medical sensors. This paper proposed a novel Intrusion Detection System (IDS) based on the network parameters, which is able to differentiate the normal state and abnormal state as false alerts from jamming state. Our proposed technique also allows us to identify three types of jamming in order to decrease the false alarms rates and increase the detection rates. Finally, this IDS mechanism is simulated in Castalia platform, which is based on the OMNET ++ simulator.