Automated and Blind Detection of Low Probability of Intercept RF Anomaly Signals
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3636534.3698243.pdf
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Author(s)
Gusain, Kuanl
Hassan, Zoheb
Couto, David
Malek, Mai Abdel
Shah, Vijay K
Zheng, Lizhong
Reed, Jeffrey H.
Date Issued
December 4, 2024
Publisher
ACM|The 30th Annual International Conference on Mobile Computing and Networking
Citation
Gusain, Kuanl, Hassan, Zoheb, Couto, David, Malek, Mai Abdel, Shah, Vijay K et al. 2024. "Automated and Blind Detection of Low Probability of Intercept RF Anomaly Signals."
Version
Final published version
Abstract
Automated spectrum monitoring necessitates the accurate detection of low probability of intercept (LPI) radio frequency (RF) anomaly signals to identify unwanted interference in wireless networks. However, detecting these unforeseen low-power RF signals is fundamentally challenging due to the scarcity of labeled RF anomaly data. In this paper, we introduce WANDA (Wireless ANomaly Detection Algorithm), an automated framework designed to detect LPI RF anomaly signals in low signal-to-interference ratio (SIR) environments without relying on labeled data. WANDA operates through a two-step process: (i) Information extraction, where a convolutional neural network (CNN) utilizing soft Hirschfeld-Gebelein-Rényi correlation (HGR) as the loss function extracts informative features from RF spectrograms; and (ii) Anomaly detection, where the extracted features are applied to a one-class support vector machine (SVM) classifier to infer RF anomalies. To validate the effectiveness of WANDA, we present a case study focused on detecting unknown Bluetooth signals within the WiFi spectrum using a practical dataset. Experimental results demonstrate that WANDA outperforms other methods in detecting anomaly signals across a range of SIR values (-10 dB to 20 dB).
Description
ACM MobiCom ’24, November 18–22, 2024, Washington D.C., DC, USA
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1145/3636534.3698243
