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Vomvas, Marinos; Blaß, Erik-Oliver; Noubir, Guevara

doi:10.1145/3448300.3468228

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…Alternative solutions to overshadowing attacks could aim to reduce the predictability of signals through cryptographic interleaving and modulation [67], however, significant changes to the standard might be required. Additional alternatives are the use of machine learning for jamming detection, for instance, by using tools to identify RF transmissions in real-time [83,84] and employing signatures that would aim at detecting anomalies in the spectrum, using deep learning to detect and cancel high power jammers [85][86][87], or localizing the source of the jamming signals [88]. However, currently there is no support for these approaches in the standard, and RF ML approaches would require additional evaluation for overshadowing scenarios.…”

Section: Sicunder: Mitigations and Evaluationmentioning

confidence: 99%

Securing wireless communications from the PHY up: a low-layer protocol approach for privacy, security, and resilience

Ludant

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Sirma for the great moments shared together during these years. I would also like to thank my friends back home, whom have continued supporting me and encouraging me during these years, and I would like to thank the Gym for keeping me mentally sane when I was doubting myself, and for giving me the mental strength to keep going.I want to thank my family for their unconditional love and support and dedicate this dissertation to them. They have always been an inspiration for me due to their hard work, and I will be always grateful for all the sacrifices they did for me to be able to pursue what I want in life. Lastly, I want to thank the best life partner I could have asked for, Chaima, for her support and love during these years, and for making me smile everyday even when I was going through tough times.4 User-Privacy Leakages in 5G Resource Scheduling Information 4.1 Essential Background Towards a 5G Sniffer .

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