COMMUNICATION BETWEEN SYNCHRONIZED RANDOM NUMBER GENERATORS

2004 ◽  
Vol 14 (11) ◽  
pp. 3995-4008 ◽  
Author(s):  
WEIGUANG YAO ◽  
PEI YU ◽  
CHRISTOPHER ESSEX
Keyword(s):  
Chaotic System ◽  
Secure Communication ◽  
Random Number ◽  
Lorenz System ◽  
Random Number Generator ◽  
Number Generator ◽  
Random Number Generators ◽  
The Lorenz System ◽  
Chaotic Carrier

In most published chaos-based communication schemes, the system's parameters used as a key could be intelligently estimated by a cracker based on the fact that information about the key is contained in the chaotic carrier. In this paper, we will show that the least significant digits (LSDs) of a signal from a chaotic system can be so highly random that the system can be used as a random number generator. Secure communication could be built between the synchronized generators nonetheless. The Lorenz system is used as an illustration.

SRAM Based Random Number Generator for Non-Repeating Pattern Generation

2014 ◽  
Vol 573 ◽  
pp. 181-186 ◽  
Author(s):  
G.P. Ramesh ◽  
A. Rajan
Keyword(s):  
Random Number ◽  
Statistical Tests ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Pattern Generation ◽  
Storage Device ◽  
Number Generator ◽  
Random Number Generators ◽  
Field Programmable ◽  
The Look

—Field-programmable gate array (FPGA) optimized random number generators (RNGs) are more resource-efficient than software-optimized RNGs because they can take advantage of bitwise operations and FPGA-specific features. A random number generator (RNG) is a computational or physical device designed to generate a sequence of numbers or symbols that lack any pattern, i.e. appear random. The many applications of randomness have led to the development of several different methods for generating random data. Several computational methods for random number generation exist, but often fall short of the goal of true randomness though they may meet, with varying success, some of the statistical tests for randomness intended to measure how unpredictable their results are (that is, to what degree their patterns are discernible).LUT-SR Family of Uniform Random Number Generators are able to handle randomness only based on seeds that is loaded in the look up table. To make random generation efficient, we propose new approach based on SRAM storage device.Keywords: RNG, LFSR, SRAM

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 Pseudo-Random Number Generator Based on Logistic Chaotic System

Entropy ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. 960 ◽  
Author(s):  
Luyao Wang ◽  
Hai Cheng
Keyword(s):  
Chaotic System ◽  
Random Number ◽  
Chaotic Behavior ◽  
Statistical Tests ◽  
Random Sequence ◽  
Random Number Generator ◽  
Statistical Characteristics ◽  
Random Number Generators ◽  
System Parameters ◽  
Pseudo Random Number

In recent years, a chaotic system is considered as an important pseudo-random source to pseudo-random number generators (PRNGs). This paper proposes a PRNG based on a modified logistic chaotic system. This chaotic system with fixed system parameters is convergent and its chaotic behavior is analyzed and proved. In order to improve the complexity and randomness of modified PRNGs, the chaotic system parameter denoted by floating point numbers generated by the chaotic system is confused and rearranged to increase its key space and reduce the possibility of an exhaustive attack. It is hard to speculate on the pseudo-random number by chaotic behavior because there is no statistical characteristics and infer the pseudo-random number generated by chaotic behavior. The system parameters of the next chaotic system are related to the chaotic values generated by the previous ones, which makes the PRNG generate enough results. By confusing and rearranging the output sequence, the system parameters of the previous time cannot be gotten from the next time which ensures the security. The analysis shows that the pseudo-random sequence generated by this method has perfect randomness, cryptographic properties and can pass the statistical tests.

Chaotic True Random Number Generator for Secure Communication Applications

2020 ◽  
Author(s):  
Alaaddin Al-Shidaifat ◽  
Chamindra Jayawickrama ◽  
Yechan Jung ◽  
Songwook-Lee ◽  
Hanjung Song ◽  
...  
Keyword(s):  
Secure Communication ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator

scholarly journals A Torus-Chaotic System and Its Pseudorandom Properties

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Jizhao Liu ◽  
Xiangzi Zhang ◽  
Qingchun Zhao ◽  
Jing Lian ◽  
Fangjun Huang ◽  
...  
Keyword(s):  
Lyapunov Exponents ◽  
Chaotic System ◽  
Cyber Security ◽  
Secure Communication ◽  
Chaotic Systems ◽  
Random Number ◽  
Current Knowledge ◽  
Random Number Generator ◽  
Qr Code ◽  
Security Systems

Exploring and investigating new chaotic systems is a popular topic in nonlinear science. Although numerous chaotic systems have been introduced in the literature, few of them focus on torus-chaotic system. The aim of our short work is to widen the current knowledge of torus chaos. In this paper, a new torus-chaotic system is proposed, which has one positive Lyapunov exponent, two zero Lyapunov exponents, and two negative Lyapunov exponents. The dynamic behavior is investigated by Lyapunov exponents, bifurcations, and stability. The analysis shows that this system has an interesting route leading to chaos. Furthermore, the pseudorandom properties of output sequence are well studied and a random number generator algorithm is proposed, which has the potential of being used in several cyber security systems such as the verification code, secure QR code, and some secure communication protocols.

A CHAOS-BASED RANDOM NUMBER GENERATOR FOR EIGHT-BIT MICRO-CONTROLLER SYSTEM

2008 ◽  
Vol 18 (03) ◽  
pp. 851-867 ◽  
Author(s):  
K. W. TANG ◽  
H. S. KWOK ◽  
WALLACE K. S. TANG ◽  
K. F. MAN
Keyword(s):  
Chaotic Systems ◽  
Random Number ◽  
Statistical Tests ◽  
Chaotic Map ◽  
Random Number Generator ◽  
High Dimensional ◽  
Number Generator ◽  
Constrained System ◽  
Random Number Generators ◽  
Consumer Markets

Random number generators are widely used in different applications. However, it is difficult to obtain a good random number generator in low precision and resource constrained system, such as an eight-bit micro-controller system which is still commonly used in industrial and consumer markets. This paper provides a practical solution for this problem based on chaotic systems. By the use of a modified Chua's circuit, it is demonstrated that the sampled state, after post-processing by a high-dimensional chaotic map, can be used as a random source even in an eight-bit environment. The randomness of the generated sequence is testified and confirmed by different statistical tests and the up-to-date statistical suite.

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