Statistical Random Number Generator Attack against the Kirchhoff-Law-Johnson-Noise (KLJN) Secure Key Exchange Protocol
Christiana Chamon, Shahriar Ferdous, and Laszlo B. Kish

TL;DR
This paper presents four new statistical attacks on the KLJN secure key exchange protocol, exploiting compromised random number generators and partial noise correlations to reveal secret keys.
Contribution
It introduces novel statistical attack methods against KLJN, demonstrating vulnerabilities when random number generators are compromised or partially known.
Findings
Eve can crack the key by cross-correlating her noise with the wire voltage.
Partial knowledge of Alice's or Bob's noise enables successful attacks.
Full attack requires the entire bit exchange period for low-error success.
Abstract
This paper introduces and demonstrates four new statistical attacks against the Kirchhoff-Law-Johnson-Noise (KLJN) secure key exchange scheme. The attacks utilize compromised random number generators at Alice's/Bob's site(s). The case of partial correlations between Alice's/Bob's and Eve's probing noises is explored, that is, Eve's knowledge of Alice's and Bob's noises is limited but not zero. We explore the bilateral situation where Eve has partial knowledge of Alice's and Bob's random number generators. It is shown that in this situation Eve can crack the secure key bit by taking the highest cross-correlation between her probing noises and the measured voltage noise in the wire. She can also crack the secure key bit by taking the highest cross-correlation between her noise voltages and her evaluation of Alice's/Bob's noise voltages. We then explore the unilateral situation in which…
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Taxonomy
TopicsAdvanced Statistical Modeling Techniques · Fractal and DNA sequence analysis
