A Physical Principle for Fast and Miniature Random Number Hardware Generator Using MPPC Photo Detector

2015 ◽  
Vol 7 (3) ◽  
pp. 1970-1975
Author(s):  
Dmitriy Beznosko
Keyword(s):  
Computer Games ◽  
High Speed ◽  
High Energy Physics ◽  
Random Number ◽  
Random Number Generator ◽  
High Energy ◽  
Physical Principle ◽  
Random Numbers ◽  
Geiger Mode ◽  
User Data

This paper presents the physical concept and test results of sample data of the high-speed hardware true random number generator design based on typically used for High Energy Physics hardware. Main features of this concept are the high speed of the true random numbers generation (tens of Mbt/s), miniature size and estimated lower production cost. This allows the use of such a device not only in large companies and government offices but for the end-user data cryptography, in classrooms, in scientific Monte-Carlo simulations, computer games and any other place where large number of true random numbers is required. The physics of the operations principle of using a Geiger-mode avalanche photo detector is discussed and the high quality of the data collected is demonstrated.

A Low-Cost Highly Reliable Spintronic True Random Number Generator Circuit for Secure Cryptography

SPIN ◽  
2019 ◽  
Vol 10 (01) ◽  
pp. 2050003 ◽  
Author(s):  
Iman Alibeigi ◽  
Abdolah Amirany ◽  
Ramin Rajaei ◽  
Mahmoud Tabandeh ◽  
Saeed Bagheri Shouraki
Keyword(s):  
High Speed ◽  
High Performance ◽  
Random Number ◽  
Low Cost ◽  
Random Number Generator ◽  
Magnetic Tunnel Junction ◽  
Random Number Generation ◽  
Cmos Technology ◽  
Random Numbers ◽  
Number Generation

Generation of random numbers is one of the most important steps in cryptographic algorithms. High endurance, high performance and low energy consumption are the attractive features offered by the Magnetic Tunnel Junction (MTJ) devices. Therefore, they have been considered as one of the promising candidates for next-generation digital integrated circuits. In this paper, a new circuit design for true random number generation using MTJs is proposed. Our proposed circuit offers a high speed, low power and a truly random number generation. In our design, we employed two MTJs that are configured in special states. Generated random bit at the output of the proposed circuit is returned to the write circuit to be written in the relevant cell for the next random generation. In a random bitstream, all bits must have the same chance of being “0”or “1”. We have proposed a new XOR-based method in this paper to resolve this issue in multiple random generators that produce truly random numbers with a different number of ones and zeros in the output stream. The simulation results using a 45[Formula: see text]nm CMOS technology with a special model of MTJ validated the advantages offered by the proposed circuit.

FPGA Implementation of Park-Miller Algorithm to Generate Sequence of 32-Bit Pseudo Random Key for Encryption and Decryption of Plain Text

2013 ◽  
Vol 2 (3) ◽  
pp. 99
Author(s):  
Bharatesh N ◽  
Rohith S
Keyword(s):  
High Speed ◽  
Random Number ◽  
Random Number Generator ◽  
Digital Circuit ◽  
Fpga Implementation ◽  
Random Numbers ◽  
Verilog Hdl ◽  
Plain Text ◽  
Booth Multiplier ◽  
Pseudo Random Number

There are many problems arises in randomized algorithms whose solutions are fundamentally based on assumptions that pure random numbers exist, so pseudo-random number generators can imitate randomness sufficiently well for most applications. The proposed scheme is a FPGA implementation of Park-Miller Algorithm for generating sequence of Pseudo-Random keys. The properties like High speed, low power and flexibility of designed PRNG(Pseudo Random Number Generator) makes any digital circuit faster and smaller. The algorithm uses a PRNG Module, it contains 32-bit Booth Multiplier, 32-bit Floating point divider and a FSM module. After generating a sequence of 32-bit Pseudo-Random numbers we have used these numbers as a key to Encrypt 128-bit plain text to become a cipher text and by using the same key to decrypt the encrypted data to get original Plain text. The Programming is done in Verilog-HDL, successfully synthesized and implemented in XILINX Spartan 3E FPGA kit.

scholarly journals A simple low-latency real-time certifiable quantum random number generator

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yanbao Zhang ◽  
Hsin-Pin Lo ◽  
Alan Mink ◽  
Takuya Ikuta ◽  
Toshimori Honjo ◽  
...  
Keyword(s):  
Real Time ◽  
High Speed ◽  
Random Number ◽  
Random Number Generator ◽  
Low Latency ◽  
Random Numbers ◽  
Number Generator ◽  
Quantum Randomness ◽  
Initial Request ◽  
Real World Applications

AbstractQuantum random numbers distinguish themselves from others by their intrinsic unpredictability arising from the principles of quantum mechanics. As such they are extremely useful in many scientific and real-world applications with considerable efforts going into their realizations. Most demonstrations focus on high asymptotic generation rates. For this goal, a large number of repeated trials are required to accumulate a significant store of certifiable randomness, resulting in a high latency between the initial request and the delivery of the requested random bits. Here we demonstrate low-latency real-time certifiable randomness generation from measurements on photonic time-bin states. For this, we develop methods to certify randomness taking into account adversarial imperfections in both the state preparation and the measurement apparatus. Every 0.12 s we generate a block of 8192 random bits which are certifiable against all quantum adversaries with an error bounded by 2−64. Our quantum random number generator is thus well suited for realizing a continuously-operating, high-security and high-speed quantum randomness beacon.

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 A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map

Micromachines ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 31
Author(s):  
Junxiu Liu ◽  
Zhewei Liang ◽  
Yuling Luo ◽  
Lvchen Cao ◽  
Shunsheng Zhang ◽  
...  
Keyword(s):  
Random Number ◽  
Chaotic Map ◽  
Logistic Map ◽  
Random Number Generator ◽  
Alternative Methods ◽  
Random Numbers ◽  
Number Generator ◽  
Stochastic Computing ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

Recent research showed that the chaotic maps are considered as alternative methods for generating pseudo-random numbers, and various approaches have been proposed for the corresponding hardware implementations. In this work, an efficient hardware pseudo-random number generator (PRNG) is proposed, where the one-dimensional logistic map is optimised by using the perturbation operation which effectively reduces the degradation of digital chaos. By employing stochastic computing, a hardware PRNG is designed with relatively low hardware utilisation. The proposed hardware PRNG is implemented by using a Field Programmable Gate Array device. Results show that the chaotic map achieves good security performance by using the perturbation operations and the generated pseudo-random numbers pass the TestU01 test and the NIST SP 800-22 test. Most importantly, it also saves 89% of hardware resources compared to conventional approaches.

scholarly journals Magniber v2 Ransomware Decryption: Exploiting the Vulnerability of a Self-Developed Pseudo Random Number Generator

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 16
Author(s):  
Sehoon Lee ◽  
Myungseo Park ◽  
Jongsung Kim
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Operation Process ◽  
User Data ◽  
Encryption Algorithms ◽  
Recovery Result ◽  
Pseudo Random Number Generator ◽  
Randomness Tests

With the rapid increase in computer storage capabilities, user data has become increasingly important. Although user data can be maintained by various protection techniques, its safety has been threatened by the advent of ransomware, defined as malware that encrypts user data, such as documents, photographs and videos, and demands money to victims in exchange for data recovery. Ransomware-infected files can be recovered only by obtaining the encryption key used to encrypt the files. However, the encryption key is derived using a Pseudo Random Number Generator (PRNG) and is recoverable only by the attacker. For this reason, the encryption keys of malware are known to be difficult to obtain. In this paper, we analyzed Magniber v2, which has exerted a large impact in the Asian region. We revealed the operation process of Magniber v2 including PRNG and file encryption algorithms. In our analysis, we found a vulnerability in the PRNG of Magniber v2 developed by the attacker. We exploited this vulnerability to successfully recover the encryption keys, which was by verified the result in padding verification and statistical randomness tests. To our knowledge, we report the first recovery result of Magniber v2-infected files.

scholarly journals RRAM Random Number Generator Based on Train of Pulses

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1831
Author(s):  
Binbin Yang ◽  
Daniel Arumí ◽  
Salvador Manich ◽  
Álvaro Gómez-Pau ◽  
Rosa Rodríguez-Montañés ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Random Access ◽  
Pulse Amplitude ◽  
Resistive Random Access Memory ◽  
Random Numbers ◽  
Number Generator ◽  
Security Applications ◽  
Device Resistance ◽  
New Strategy

In this paper, the modulation of the conductance levels of resistive random access memory (RRAM) devices is used for the generation of random numbers by applying a train of RESET pulses. The influence of the pulse amplitude and width on the device resistance is also analyzed. For each pulse characteristic, the number of pulses required to drive the device to a particular resistance threshold is variable, and it is exploited to extract random numbers. Based on this behavior, a random number generator (RNG) circuit is proposed. To assess the performance of the circuit, the National Institute of Standards and Technology (NIST) randomness tests are applied to evaluate the randomness of the bitstreams obtained. The experimental results show that four random bits are simultaneously obtained, passing all the applied tests without the need for post-processing. The presented method provides a new strategy to generate random numbers based on RRAMs for hardware security applications.

scholarly journals Self-clocking fast and variation tolerant true random number generator based on a stochastic mott memristor

2020 ◽  
Author(s):  
Gwangmin Kim ◽  
Jae Hyun In ◽  
Hakseung Rhee ◽  
Woojoon Park ◽  
Hanchan Song ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Harsh Environments ◽  
Random Numbers ◽  
Number Generator ◽  
High Tolerance ◽  
Stochastic Oscillation ◽  
Advanced Method ◽  
Intrinsic Stochasticity

Abstract The intrinsic stochasticity of the memristor can be used to generate true random numbers, essential for non-decryptable hardware-based security devices. Here we propose a novel and advanced method to generate true random numbers utilizing the stochastic oscillation behavior of a NbOx mott memristor, exhibiting self-clocking, fast and variation tolerant characteristics. The random number generation rate of the device can be at least 40 kbs-1, which is the fastest record compared with previous volatile memristor-based TRNG devices. Also, its dimensionless operating principle provides high tolerance against both ambient temperature variation and device-to-device variation, enabling robust security hardware applicable in harsh environments.

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