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Govind Singh

Publications and source records attributed to Govind Singh.

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WiFiSpectralJam: A Large-Scale Open Wi-Fi Spectral Scan Dataset with Controlled RF Jamming

WiFiSpectralJam is a Wi-Fi spectral-scan dataset comprising 14.52 GB, 96,090 CSV files, and 522,771,130 ordered spectral observations using commodity Wi-Fi sensing hardware. Measurements were acquired with a Raspberry Pi Compute Module 4 equipped with a Qualcomm Atheros QCA9880 802.11ac network interface and the Linux ath10k spectral-scan interface. The dataset spans active and passive scan modalities across the 2.4 and 5 GHz bands and includes real-world benign background captures, benign RF-chamber floor captures, and controlled RF-jamming captures generated with a HackRF One. Jamming conditions vary by transmit power, target channel, and, in the active subset, waveform type. The release provides the raw spectral-scan records together with a file-level metadata manifest, derived spectral-summary features, validation outputs, and reproducible benchmark protocols. These resources support reuse in RF interference characterisation, jamming detection, spectrum monitoring, distribution-shift evaluation, and machine-learning studies using commodity-NIC spectral measurements. The dataset is publicly available at: https://www.kaggle.com/datasets/daniaherzalla/radio-frequency-jamming/data.

cs.NI

Benchmarking and Security Considerations of Wi-Fi FTM for Ranging in IoT Devices

The IEEE 802.11mc standard introduces fine time measurement (Wi-Fi FTM), allowing high-precision synchronization between peers and round-trip time calculation (Wi-Fi RTT) for location estimation - typically with a precision of one to two meters. This has considerable advantages over received signal strength (RSS)-based trilateration, which is prone to errors due to multipath reflections. We examine different commercial radios which support Wi-Fi RTT and benchmark Wi-Fi FTM ranging over different spectrums and bandwidths. Importantly, we find that while Wi-Fi FTM supports localization accuracy to within one to two meters in ideal conditions during outdoor line-of-sight experiments, for indoor environments at short ranges similar accuracy was only achievable on chipsets supporting Wi-Fi FTM on wider (VHT80) channel bandwidths rather than narrower (HT20) channel bandwidths. Finally, we explore the security implications of Wi-Fi FTM and use an on-air sniffer to demonstrate that Wi-Fi FTM messages are unprotected. We consequently propose a threat model with possible mitigations and directions for further research.

cs.NI