Title
Highly Efficient Known-Plaintext Attacks Against Orthogonal Blinding Based Physical Layer Security
Abstract
In this letter, we describe highly effective known-plaintext attacks against physical layer security schemes. We substantially reduce the amount of required known-plaintext symbols and lower the symbol error rate (SER) for the attacker. In particular, we analyze the security of orthogonal blinding schemes that disturb an eavesdropper's signal reception using artificial noise transmission. We improve the attack efficacy using fast converging optimization algorithms and combining the measurements of neighboring subchannels in a multicarrier system. We implement the enhanced attack algorithms by solving unregularized and regularized least squares problems. By means of simulation, we show that the performance of the new attack algorithms supersedes the normalized least mean square approach discussed in the work of Schulz et al., e.g., by lowering the eavesdropper's SER by 82% while using 95% less known plaintext.
Year
DOI
Venue
2015
10.1109/LWC.2014.2363176
IEEE Wireless Commun. Letters
Keywords
Field
DocType
optimisation,known-plaintext attack,ser,regularized least squares problems,neighboring subchannel measurements,eavesdropper signal reception,cryptography,$ell_{1}$ regularization,artificial noise transmission,orthogonal blinding,symbol error rate,fast converging optimization algorithms,attack efficacy,plaintext symbols,cholesky update,normalized least mean square approach,multicarrier system,l1 regularization,least squares approximations,enhanced attack algorithms,physical layer security,telecommunication security,orthogonal blinding based physical layer security schemes,highly efficient known-plaintext attacks,unregularized least squares problems,modulation,security,wireless communication,physical layer,convergence,noise
Convergence (routing),Least mean squares filter,Wireless,Blinding,Computer science,Known-plaintext attack,Computer network,Modulation,Physical layer,Artificial noise
Journal
Volume
Issue
ISSN
4
1
2162-2337
Citations 
PageRank 
References 
4
0.48
4
Authors
5
Name
Order
Citations
PageRank
Yao Zheng1274.41
Matthias Schulz211112.74
Wenjing Lou37822328.18
Yiwei Thomas Hou42825169.32
Matthias Hollick575097.29