Real-Time Jamming Detection in Wireless IoT Networks
IoT-based networks are vulnerable to jamming attacks due to their large-scale deployment and shared communication environment. Resource constraints and the low computational power of IoT devices make it harder to implement high-performance ML-based architectures for jamming detection. In this work,...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10175509/ |
| _version_ | 1797772627372146688 |
|---|---|
| author | Fatima Tu Zahra Yavuz Selim Bostanci Mujdat Soyturk |
| author_facet | Fatima Tu Zahra Yavuz Selim Bostanci Mujdat Soyturk |
| author_sort | Fatima Tu Zahra |
| collection | DOAJ |
| description | IoT-based networks are vulnerable to jamming attacks due to their large-scale deployment and shared communication environment. Resource constraints and the low computational power of IoT devices make it harder to implement high-performance ML-based architectures for jamming detection. In this work, the effects of jamming attacks on a Wi-Fi network are presented and a novel real-time jamming detection mechanism is devised which can identify attacks on multiple channels in 2.4 GHz bandwidth simultaneously. The experiments are conducted in the lab environment by generating the jamming attacks with a Software Defined Radio. Certain QoS parameters in an end-to-end wireless IoT system are collected during normal operating conditions and during jamming attacks. The detection mechanism is implemented on IoT devices by employing the effects of jamming on wireless communication. The proposed real-time jamming detection method has an accuracy of 99% with zero false alarms. It benefits from the communication profile of a wireless network to detect jamming and requires minimal computational resources regarding memory and CPU usage which makes it a low-cost and easily deployable solution for IoT devices. |
| first_indexed | 2024-03-12T21:53:42Z |
| format | Article |
| id | doaj.art-f6297b5d10054015ab4f83e043411cb8 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-12T21:53:42Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f6297b5d10054015ab4f83e043411cb82023-07-25T23:00:48ZengIEEEIEEE Access2169-35362023-01-0111704257044210.1109/ACCESS.2023.329340410175509Real-Time Jamming Detection in Wireless IoT NetworksFatima Tu Zahra0https://orcid.org/0000-0002-4907-4655Yavuz Selim Bostanci1Mujdat Soyturk2https://orcid.org/0000-0003-2612-1460Vehicular Networking and Intelligent Transportation Systems Research Laboratory, Marmara University, İstanbul, TurkeyVehicular Networking and Intelligent Transportation Systems Research Laboratory, Marmara University, İstanbul, TurkeyVehicular Networking and Intelligent Transportation Systems Research Laboratory, Marmara University, İstanbul, TurkeyIoT-based networks are vulnerable to jamming attacks due to their large-scale deployment and shared communication environment. Resource constraints and the low computational power of IoT devices make it harder to implement high-performance ML-based architectures for jamming detection. In this work, the effects of jamming attacks on a Wi-Fi network are presented and a novel real-time jamming detection mechanism is devised which can identify attacks on multiple channels in 2.4 GHz bandwidth simultaneously. The experiments are conducted in the lab environment by generating the jamming attacks with a Software Defined Radio. Certain QoS parameters in an end-to-end wireless IoT system are collected during normal operating conditions and during jamming attacks. The detection mechanism is implemented on IoT devices by employing the effects of jamming on wireless communication. The proposed real-time jamming detection method has an accuracy of 99% with zero false alarms. It benefits from the communication profile of a wireless network to detect jamming and requires minimal computational resources regarding memory and CPU usage which makes it a low-cost and easily deployable solution for IoT devices.https://ieeexplore.ieee.org/document/10175509/IoTjamming detectionwireless communicationWiFiSDRreal-time |
| spellingShingle | Fatima Tu Zahra Yavuz Selim Bostanci Mujdat Soyturk Real-Time Jamming Detection in Wireless IoT Networks IEEE Access IoT jamming detection wireless communication WiFi SDR real-time |
| title | Real-Time Jamming Detection in Wireless IoT Networks |
| title_full | Real-Time Jamming Detection in Wireless IoT Networks |
| title_fullStr | Real-Time Jamming Detection in Wireless IoT Networks |
| title_full_unstemmed | Real-Time Jamming Detection in Wireless IoT Networks |
| title_short | Real-Time Jamming Detection in Wireless IoT Networks |
| title_sort | real time jamming detection in wireless iot networks |
| topic | IoT jamming detection wireless communication WiFi SDR real-time |
| url | https://ieeexplore.ieee.org/document/10175509/ |
| work_keys_str_mv | AT fatimatuzahra realtimejammingdetectioninwirelessiotnetworks AT yavuzselimbostanci realtimejammingdetectioninwirelessiotnetworks AT mujdatsoyturk realtimejammingdetectioninwirelessiotnetworks |