A True Random Number Generator with Built-in Attack Detection

Fechner, Bernhard; Osterloh, Andre

doi:10.1109/depcos-relcomex.2008.10

Cited by 3 publications

(2 citation statements)

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“…This work deals with TRNG and is an extension and abstraction to the paper presented by Fechner (2008). In contrary to pseudo RNGs (PRNGs), e.g., based on linear congruency (Knuth, 1997) or the Mersenne Twister (Matsumoto and Kurita, 1992), TRNGs are able to produce a non-periodic sequence of bits.…”

Section: Related Workmentioning

confidence: 99%

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A meta-level true random number generator

Fechner

Osterloh²

2010

IJCCBS

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True random number generators (TRNGs) are extensively used in cryptography, simulations and statistics. In this work, we introduce, extend and analyse the concept of the randomised bit cell (RBC), introducing a second meta-level of randomisation, being able to simultaneously produce random numbers and detect active non-intrusive attacks. The concept is extended by using a corrector. Meta-stability is one way to generate true random numbers. By using electromagnetic radiation, a flip-flop (ff) in a meta-stable state can be manipulated to a known state. We clarify and comprehend open issues of meta-stable ffs such as power consumption and electromagnetic field strength. The experimental comparison though a software simulation with a standard TRNG yields a 17.69 times better distribution of zeros and ones while the TRNGs are under attack at the expense of a delay which is proportional to the quality of the random source.

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Section: Related Workmentioning

confidence: 99%

“…Note, that we are also able to detect local manipulations. A mechanism to detect permanent faults through manipulation of the attack signal is use dual-rail-logic (Fechner and Osterloh, 2008). In this case, every stuck-at fault is detected by comparing both signals by using an external circuit within the perfection core.…”

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confidence: 99%