Joshua Smailes (University of Oxford), Edd Salkield (University of Oxford), Sebastian Köhler (University of Oxford), Simon Birnbach (University of Oxford), Martin Strohmeier (Cyber-Defence Campus, armasuisse S+T), Ivan Martinovic (University of Oxford)

In the wake of increasing numbers of attacks on radio communication systems, a range of techniques are being deployed to increase the security of these systems. One such technique is radio fingerprinting, in which the transmitter can be identified and authenticated by observing small hardware differences expressed in the signal. Fingerprinting has been explored in particular in the defense of satellite systems, many of which are insecure and cannot be retrofitted with cryptographic security.

In this paper, we evaluate the effectiveness of radio fingerprinting techniques under interference and jamming attacks, usually intended to deny service. By taking a pre-trained fingerprinting model and gathering a new dataset in which different levels of Gaussian noise and tone jamming have been added to the legitimate signal, we assess the attacker power required in order to disrupt the transmitter fingerprint such that it can no longer be recognized. We compare this to Gaussian jamming on the data portion of the signal, obtaining the remarkable result that transmitter fingerprints are still recognizable even in the presence of moderate levels of noise. Through deeper analysis of the results, we conclude that it takes a similar amount of jamming power in order to disrupt the fingerprint as it does to jam the message contents itself, so it is safe to include a fingerprinting system to authenticate satellite communication without opening up the system to easier denial-of-service attacks.

View More Papers

Binary Code Patching: An Ancient Art Refined for the...

Dr. Barton P. Miller (Vilas Distinguished Achievement Professor at The University of Wisconsin-Madison)

Read More

Parrot-Trained Adversarial Examples: Pushing the Practicality of Black-Box Audio...

Rui Duan (University of South Florida), Zhe Qu (Central South University), Leah Ding (American University), Yao Liu (University of South Florida), Zhuo Lu (University of South Florida)

Read More

HistCAN: A real-time CAN IDS with enhanced historical traffic...

Shuguo Zhuo, Nuo Li, Kui Ren (The State Key Laboratory of Blockchain and Data Security, Zhejiang University)

Read More

Transforming Raw Authentication Logs into Interpretable Events

Seth Hastings, Tyler Moore, Corey Bolger, Philip Schumway (University of Tulsa)

Read More