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EM radiation analysis on true random number generators: Frequency and localization retrieval method

Pierre Bayon, Lilian Bossuet, Alain Aubert, Viktor Fischer

Published May 23, 2013• 2 citations
OpenAlex

Abstract

True random number generators (TRNGs) are significant piece of hardware security that are used to generate secret keys, initial values or random masks for counter measures against side-channel attacks. Thus the security of implementation in hardware of such block is crucial. The work presented in this paper show that it is possible to find information on a TRNG using its electromagnetic radiations. The proposed analysis is suitable to retrieve information on the localization, oscillator frequency and sampling frequency of the TRNG.

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True random number generators (TRNGs) are significant piece of hardware security that are used to generate secret keys, initial values or random masks for counter measures against side-channel attacks. Thus the security of implementation in hardware of such block is crucial. The work presented in this paper show that it is possible to find information on a TRNG using its electromagnetic radiations. The proposed analysis is suitable to retrieve information on the localization, oscillator frequency and sampling frequency of the TRNG.
Random numbers play a central role in cryptography, cyber security, and gaming applications. Extracting bits from some random natural activity is one of the primitive ways to generate random numbers. True random number generator(TRNG) and quantum random number generator(QRNG) are examples of this random number sequence. The development of quantum technology made it possible to extract random sequences from quantum entropy sources. This sequence is called quantum random numbers and the whole setup is named a quantum random number generator. A suitable sampling and a physical device for the entropy source are the building blocks for a TRNG. Here we present a comparative analysis of two random number generators. Apart from the conventional statistical test for randomness, here we introduce a straightforward coefficient based on the concept of non-linearity of the Boolean function to determine the availability of any linearity in a chosen random binary sequence. It reveals the cryptographic suitability of the generated sequence w.r.t any correlation attack. A comparison of the nonlinearity of two Boolean sequences generated from two different random sources is presented.
The key point of cryptography is cryptographic algorithms and keys. The random number generator is used to generate seeds and keys randomly in many cryptographic systems. For this reason, it is essential to use keys to encrypt and decrypt the transferring information, and the security of these keys is closely related to the security of 5G network. We propose a true random number generator (TRNG) method in this paper, and are using visible spectrum for noise source. We consider that if the cryptography system utilizes data of visible spectrum using the proposed TRNG, and the TRNG generates random numbers with high entropy.
Most hardware "true" random number generators (TRNGs) take advantage of the thermal agitation around a flip-flop metastable state. In field programmable gate arrays (FPGAs), the classical TRNG structure uses two clocks, either from a PLL or from ring oscillators, in order to sample one by the other. This creates good TRNGs albeit limited in frequency by the interference rate which cannot exceed a few Mbit/s. This article presents an architecture allowing higher bit rates while maintaining provable unconditional security. This requirement becomes stringent for secure communication applications such as the cryptographic quantum key distribution (QKD) protocols. The proposed architecture is very simple as it is based on an open loop structure without any specific component such as PLLs.
Random number generators (RNG) are an important resource in many areas: cryptography (both quantum and classical), probabilistic computation (Monte Carlo methods), numerical simulations, industrial testing and labeling, hazard games, scientific research, etc. Because today's computers are deterministic, they can not create random numbers unless complemented with a RNG. Randomness of a RNG can be precisely, scientifically characterized and measured. Especially valuable is the information-theoretic provable RNG (True RNG - TRNG) which, at state of the art, seem to be possible only by use of physical randomness inherent to certain (simple) quantum systems. On the other hand, current industry standard dictates use of RNG's based on free running oscillators (FRO) whose randomness is derived from electronics noise present in logic circuits and which cannot be strictly proven. This approach is currently used in 3-rd and 4-th generation FPGA and ASIC hardware, unsuitable for realization of quantum TRNG. We compare weak and strong aspects of the two approaches and discuss possibility of building quantum TRNG in the recently appeared Mixed Signal FPGA technology. Finally, we discuss several examples where use of a TRNG is critical and show how it can significantly improve security of cryptographic systems.
This paper presents a lightweight true random number generator (TRNG) using beta radiation that is useful for Internet of Things (IoT) security. In general, a random number generator (RNG) is required for all secure communication devices because random numbers are needed to generate encryption keys. Most RNGs are computer algorithms and use physical noise as their seed. However, it is difficult to obtain physical noise in small IoT devices. Since IoT security functions are required in almost all countries, IoT devices must be equipped with security algorithms that can pass the cryptographic module validation programs of each country. In this regard, it is very cumbersome to embed security algorithms, random number generation algorithms, and even physical noise sources in small IoT devices. Therefore, this paper introduces a lightweight TRNG comprising a thin-film beta-radiation source and integrated circuits (ICs). Although the ICs are currently being designed, the IC design was functionally verified at the board level. Our random numbers are output from a verification board and tested according to National Institute of Standards and Technology standards.
Wireless networks need more security in comparison to the other networks due to their intrinsic vulnerabilities to possible attacks. It is expected that by using a distributed method for true random number generators (TRNG) in wireless sensor networks (WSN) and wireless LAN (WLAN) randomness quality of generated numbers can be enhanced. We analyze a protocol for a distributed TRNG named ScatterLight (L. R. Giuseppe, M. Fabrizio and O. Marco, 2011) for a WSN. After making some changes on ScatterLight structure and physical data sources, the Enhanced ScatterLight protocol is introduced; it provides secure and high qualified true random numbers. Thus, the quality of randomness of obtained random numbers using National Institute of Standards and Technology tests is evaluated. Finally, by analyzing the results, it can be conducted that Enhanced ScatterLight protocol in comparisons with ScatterLight protocol in WLAN and LAN provides 60% and 53% better randomness quality respectively, while the performance is equal in both protocols.