Deep Predictive Coding Neural Network for RF Anomaly Detection in Wireless Networks

Intrusion detection has become one of the most critical tasks in a wireless network to prevent service outages that can take long to fix. The sheer variety of anomalous events necessitates adopting cognitive anomaly detection methods instead of the traditional signature-based detection techniques. This paper proposes an anomaly detection methodology for wireless systems that is based on monitoring and analyzing radio frequency (RF) spectrum activities. Our detection technique leverages an existing solution for the video prediction problem, and uses it on image sequences generated from monitoring the wireless spectrum. The deep predictive coding network is trained with images corresponding to the normal behavior of the system, and whenever there is an anomaly, its detection is triggered by the deviation between the actual and predicted behavior. For our analysis, we use the images generated from the time-frequency spectrograms and spectral correlation functions of the received RF signal. We test our technique on a dataset which contains anomalies such as jamming, chirping of transmitters, spectrum hijacking, and node failure, and evaluate its performance using standard classifier metrics: detection ratio, and false alarm rate. Simulation results demonstrate that the proposed methodology effectively detects many unforeseen anomalous events in real time. We discuss the applications, which encompass industrial IoT, autonomous vehicle control and mission-critical communications services.Comment: 7 pages, 7 figures, Communications Workshop ICC'1

Secure thermal infrared communications using engineered blackbody radiation

The thermal (emitted) infrared frequency bands, from 20–40 THz and 60–100 THz, are best known for applications in thermography. This underused and unregulated part of the spectral range offers opportunities for the development of secure communications. The ‘THz Torch' concept was recently presented by the authors. This technology fundamentally exploits engineered blackbody radiation, by partitioning thermally-generated spectral noise power into pre-defined frequency channels; the energy in each channel is then independently pulsed modulated and multiplexing schemes are introduced to create a robust form of short-range secure communications in the far/mid infrared. To date, octave bandwidth (25–50 THz) single-channel links have been demonstrated with 380 bps speeds. Multi-channel ‘THz Torch' frequency division multiplexing (FDM) and frequency-hopping spread-spectrum (FHSS) schemes have been proposed, but only a slow 40 bps FDM scheme has been demonstrated experimentally. Here, we report a much faster 1,280 bps FDM implementation. In addition, an experimental proof-of-concept FHSS scheme is demonstrated for the first time, having a 320 bps data rate. With both 4-channel multiplexing schemes, measured bit error rates (BERs) of < 10(−6) are achieved over a distance of 2.5 cm. Our approach represents a new paradigm in the way niche secure communications can be established over short links

Electrocommunication for weakly electric fish

This paper addresses the problem of the electro-communication for weakly electric fish. In particular we aim at sheding light on how the fish circumvent the jamming issue for both electro-communication and active electro-sensing. A real-time tracking algorithm is presented