scholarly journals A new computer-controlled platform for ADC-based true random number generator and its applications

2019 ◽  
pp. 847-860 ◽  
Author(s):  
SELÇUK COŞKUN ◽  
İHSAN PEHLİVAN ◽  
AKİF AKGÜL ◽  
BİLAL GÜREVİN
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Digital Data ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Random Number Generators ◽  
True Random Number Generator ◽  
Sample Application ◽  
Computer Controlled ◽  
Entropy Source

The basis of encryption techniques is random number generators (RNGs). The application areas of cryptology are increasing in number due to continuously developing technology, so the need for RNGs is increasing rapidly, too. RNGs can be divided into two categories as pseudorandom number generator (PRNGs) and true random number generator (TRNGs). TRNGs are systems that use unpredictable and uncontrollable entropy sources and generate random numbers. During the design of TRNGs, while analog signals belonging to the used entropy sources are being converted to digital data, generally comparators, flip-flops, Schmitt triggers, and ADCs are used. In this study, a computer-controlled new and flexible platform to find the most appropriate system parameters in ADC-based TRNG designs is designed and realized. As a sample application with this new platform, six different TRNGs that use three different outputs of Zhongtang, which is a continuous time chaotic system, as an entropy source are designed. Random number series generated with the six designed TRNGs are put through the NIST800–22 test, which has the internationally highest standards, and they pass all tests. With the help of the new platform designed, ADC-based high-quality TRNGs can be developed fast and also without the need for expertise. The platform has been designed to decide which entropy source and parameter are better by comparing them before complex embedded TRNG designs. In addition, this platform can be used for educational purposes to explain how to work an ADC-based TRNG. That is why it can be utilized as an experiment set in engineering education, as well.

scholarly journals A Fully Digital True Random Number Generator with Entropy Source Based in Frequency Collapse

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ronaldo Serrano ◽  
Ckristian Duran ◽  
Trong-Thuc Hoang ◽  
Marco Sarmiento ◽  
Khai-Duy Nguyen ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator ◽  
Entropy Source

scholarly journals Novel Memristor Based True Random Number Generator

2020 ◽  
Author(s):  
Scott Stoller
Keyword(s):  
Random Number ◽  
Statistical Tests ◽  
Random Number Generator ◽  
Circuit Board ◽  
Random Numbers ◽  
Number Generator ◽  
Random Number Generators ◽  
Coin Toss ◽  
True Random Number Generator ◽  
Digital World

Random numbers are an important, but often overlooked part of the modern computing environment. They are used everywhere around us for a variety of purposes, from simple decision making in video games such as a coin toss, to securing financial transactions and encrypting confidential communications. They are even useful for gambling and the lottery. Random numbers are generated in many ways. Pseudo random number generators (PRNGs) generate numbers based on a formula. True random number generators (TRNGs) capture entropy from the environment to generate randomness. As our society and our devices become more connected in the digital world, it is important to develop new ways to generate truly random numbers in order to secure communications and connected devices. In this work a novel memristor-based True Random Number Generator is designed and a physical implementation is fabricated and tested using a W-based self-directed channel (SDC) memristor. The circuit was initially designed and prototyped on a breadboard. A custom Printed Circuit Board (PCB) was fabricated for the final circuit design and testing of the novel memristor-based TRNG. The National Institute of Standards and Technology (NIST) Statistical Test Suite (STS) was used to check the output of the TRNG for randomness. The TRNG was demonstrated to pass 13 statistical tests out of the 15 in the STS.

Design of True Random Number Generator Using Fingerprint as an Entropy Source and Its Implementation in S-Box

2021 ◽  
pp. 2150285
Author(s):  
Dhirendra Kumar ◽  
Utkarsh Kumar Chaurasia ◽  
Shreyansh Mishra ◽  
Prafull Singh Patel ◽  
Prasanna Kumar Misra ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Binary Sequences ◽  
Advanced Encryption Standard ◽  
Number Generator ◽  
Substitution Box ◽  
True Random Number Generator ◽  
Random Arrangement ◽  
Binary Format ◽  
Entropy Source

This paper deals with the design of a true random number generator (TRNG) using the fingerprint as an entropy source and its implementation in substitution box (S-box) of Advanced Encryption Standard (AES). Considering fingerprint as a unique and random arrangement of minutiae, these minutiae points are used as the source of entropy. The proposed design utilizes fewer resources minimizing hardware redundancy and enhancing the level of randomness. This TRNG has been designed and validated using Artix-7 FPGA. The data rate, speed and latency have been obtained as 40 Mbps, 5 Mbps and 305 ns, respectively. The generated random bit stream had also been sampled and converted to a binary format in MATLAB and tested through the National Institute of Standards and Technology (NIST) 800.22 statistical suite for validation. The proposed TRNG design pass efficiency achieved is more than 95% for a sample size of 10 binary sequences.

scholarly journals Random-telegraph-noise-enabled true random number generator for hardware security

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
James Brown ◽  
Jian Fu Zhang ◽  
Bo Zhou ◽  
Mehzabeen Mehedi ◽  
Pedro Freitas ◽  
...  
Keyword(s):  
Power Consumption ◽  
Cyber Security ◽  
Random Number ◽  
Random Number Generator ◽  
Cmos Technology ◽  
Number Generator ◽  
Random Number Generators ◽  
True Random Number Generator ◽  
Telegraph Noise ◽  
Cmos Transistor

Abstract The future security of Internet of Things is a key concern in the cyber-security field. One of the key issues is the ability to generate random numbers with strict power and area constrains. “True Random Number Generators” have been presented as a potential solution to this problem but improvements in output bit rate, power consumption, and design complexity must be made. In this work we present a novel and experimentally verified “True Random Number Generator” that uses exclusively conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bitrate, and power consumption. It uses the inherent randomness of telegraph noise in the channel current of a single CMOS transistor as an entropy source. For the first time multi-level and abnormal telegraph noise can be utilised, which greatly reduces device selectivity and offers much greater bitrates. The design is verified using a breadboard and FPGA proof of concept circuit and passes all 15 of the NIST randomness tests without any need for post-processing of the generated bitstream. The design also shows resilience against machine learning attacks performed by the LSTM neural network.

Pyramid Entropy Source for True Random Number Generator on FPGA

2020 ◽  
pp. 23-33
Author(s):  
Sivaraman Rethinam ◽  
Sundararaman Rajagopalan ◽  
Sridevi Arumugham ◽  
Siva Janakiraman ◽  
C. Lakshmi ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator ◽  
Entropy Source

scholarly journals Random Numbers Generated from Audio and Video Sources

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
I-Te Chen
Keyword(s):  
Chaos Theory ◽  
Random Number ◽  
Statistical Tests ◽  
Random Number Generator ◽  
Random Numbers ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Random Number Generators ◽  
Video File ◽  
Recognition Probability

Random numbers are very useful in simulation, chaos theory, game theory, information theory, pattern recognition, probability theory, quantum mechanics, statistics, and statistical mechanics. The random numbers are especially helpful in cryptography. In this work, the proposed random number generators come from white noise of audio and video (A/V) sources which are extracted from high-resolution IPCAM, WEBCAM, and MPEG-1 video files. The proposed generator applied on video sources from IPCAM and WEBCAM with microphone would be the true random number generator and the pseudorandom number generator when applied on video sources from MPEG-1 video file. In addition, when applying NIST SP 800-22 Rev.1a 15 statistics tests on the random numbers generated from the proposed generator, around 98% random numbers can pass 15 statistical tests. Furthermore, the audio and video sources can be found easily; hence, the proposed generator is a qualified, convenient, and efficient random number generator.

0.4 mW, 0.27 pJ/bit true random number generator using jitter, metastability and current starved topology

2020 ◽  
Vol 14 (7) ◽  
pp. 1001-1011
Author(s):  
Dhirendra Kumar ◽  
Rahul Anand ◽  
Sajai Vir Singh ◽  
Prasanna Kumar Misra ◽  
Ashok Srivastava ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator

scholarly journals A High‐Speed True Random Number Generator Based on a Cu x Te 1− x Diffusive Memristor

2021 ◽  
pp. 2100062
Author(s):  
Kyung Seok Woo ◽  
Jaehyun Kim ◽  
Janguk Han ◽  
Jin Myung Choi ◽  
Woohyun Kim ◽  
...  
Keyword(s):  
High Speed ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator

scholarly journals True Random Number Generator Based on Fibonacci-Galois Ring Oscillators for FPGA

2021 ◽  
Vol 11 (8) ◽  
pp. 3330
Author(s):  
Pietro Nannipieri ◽  
Stefano Di Matteo ◽  
Luca Baldanzi ◽  
Luca Crocetti ◽  
Jacopo Belli ◽  
...  
Keyword(s):  
Field Programmable Gate Array ◽  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Galois Ring ◽  
Number Generator ◽  
True Random Number Generator ◽  
Number Generation ◽  
Field Programmable ◽  
Gate Array

Random numbers are widely employed in cryptography and security applications. If the generation process is weak, the whole chain of security can be compromised: these weaknesses could be exploited by an attacker to retrieve the information, breaking even the most robust implementation of a cipher. Due to their intrinsic close relationship with analogue parameters of the circuit, True Random Number Generators are usually tailored on specific silicon technology and are not easily scalable on programmable hardware, without affecting their entropy. On the other hand, programmable hardware and programmable System on Chip are gaining large adoption rate, also in security critical application, where high quality random number generation is mandatory. The work presented herein describes the design and the validation of a digital True Random Number Generator for cryptographically secure applications on Field Programmable Gate Array. After a preliminary study of literature and standards specifying requirements for random number generation, the design flow is illustrated, from specifications definition to the synthesis phase. Several solutions have been studied to assess their performances on a Field Programmable Gate Array device, with the aim to select the highest performance architecture. The proposed designs have been tested and validated, employing official test suites released by NIST standardization body, assessing the independence from the place and route and the randomness degree of the generated output. An architecture derived from the Fibonacci-Galois Ring Oscillator has been selected and synthesized on Intel Stratix IV, supporting throughput up to 400 Mbps. The achieved entropy in the best configuration is greater than 0.995.

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