Memristor based ring oscillators true random number generator with different window functions for applications in cryptography

Abstract

<span>Cryptographic applications require numbers that are random and pseudorandom. Keys must be produced in a random manner in order to be used in common cryptosystems. Random or pseudorandom inputs at different terminals are also required in a lot of cryptographic protocols. For example, producing digital signatures using supporting quantities or in verification procedures that requires generating challenges. Random number generation is an important part of cryptography because there are flaws in random number generation that can be taken advantage by attackers that compromised encryption systems that are algorithmically secure. True random number generators (TRNGs) are the best in producing random numbers. This paper presents a True Random Number Generator that uses memristor based ring oscillators in the design. The designs are implemented in 0.18 µm complementary metal oxide semiconductor (CMOS) technology using LT SPICE IV. Different window functions for the memristor model was applied to the TRNG and compared. Statistical tests results of the output random numbers produced showed that the proposed TRNG design can produce random output regardless of the window function.</span>

Demonstration of Three True Random Number Generator Circuits Using Memristor Created Entropy and Commercial Off-the-Shelf Components

“…Random numbers have a variety of uses in modern computing and information security, ranging from simple decision making in a video game, to encryption of secure documents and keeping banking transactions secure [ 1 , 2 , 3 , 4 , 5 , 6 ]. The security of data and communication channels is especially important today with the increase in connected devices throughout the world.…”

“…TRNGs can be implemented in many ways. Examples of TRNGs include measuring the time between clicks on a Geiger counter [ 10 ], measuring frequencies or latencies of asynchronous events on a PC [ 11 , 12 ] and circuits comprised of oscillators where entropy is captured as jitter [ 3 , 4 , 5 , 7 , 13 , 14 , 15 , 16 ]. Even modern CPUs can have dedicated hardware on the application specific integrated circuit (ASIC) to capture entropy [ 17 ].…”

“…A recent approach in TRNG circuits has been to use a memristor device [ 18 , 19 , 20 ] to capture entropy for TRNG circuit designs [ 1 , 2 , 5 , 6 , 15 , 21 , 22 , 23 ]. Many of these designs use the memristors in a circuit that oscillates (e.g., a ring oscillator) or is driven by a pulse generator.…”

“…Last, we build a memristor-based TRNG circuit of our own design and put it through the same tests in order to demonstrate the ease of implementation of memristor-based TRNGs and their accessibility to anyone using commercially available components. While there are other statistical test suites available to test the randomness of RNGs, the NIST STS had the most widespread use in our literature survey, having been used to assess RNGs in [ 1 , 2 , 5 , 6 , 7 , 8 , 14 , 15 , 16 ]. A brief description of each test in the NIST STS can be found in Appendix A .…”

Design and implementation of proposed 320 bit RC6-cascaded encryption/decryption cores on altera FPGA

“…It is one among various symmetric-key block ciphers used to provide security efficiently and with flexibility. There are some types such as Blowfish, Twofish, RC6, Rijndael, Mars, Serpent and DES, which have been received with the greatest practical interest [1][2][3][4].…”