scholarly journals A Novel Intermittent Jumping Coupled Map Lattice Based on Multiple Chaotic Maps

2021 ◽  
Vol 11 (9) ◽  
pp. 3797
Author(s):  
Rong Huang ◽  
Fang Han ◽  
Xiaojuan Liao ◽  
Zhijie Wang ◽  
Aihua Dong
Keyword(s):  
Parameter Space ◽  
Random Number ◽  
Chaotic Maps ◽  
Chaotic Behavior ◽  
Random Number Generator ◽  
Coupled Map Lattice ◽  
Number Generator ◽  
Multiple Chaotic Maps ◽  
Image Cryptosystem ◽  
Pseudo Random Number Generator

Coupled Map Lattice (CML) usually serves as a pseudo-random number generator for encrypting digital images. Based on our analysis, the existing CML-based systems still suffer from problems like limited parameter space and local chaotic behavior. In this paper, we propose a novel intermittent jumping CML system based on multiple chaotic maps. The intermittent jumping mechanism seeks to incorporate the multi-chaos, and to dynamically switch coupling states and coupling relations, varying with spatiotemporal indices. Extensive numerical simulations and comparative studies demonstrate that, compared with the existing CML-based systems, the proposed system has a larger parameter space, better chaotic behavior, and comparable computational complexity. These results highlight the potential of our proposal for deployment into an image cryptosystem.

scholarly journals A New Pseudo-Random Number Generator Based on Two Chaotic Maps

Informatica ◽  
2013 ◽  
Vol 24 (2) ◽  
pp. 181-197 ◽  
Author(s):  
Michael Francois ◽  
Thomas Grosges ◽  
Dominique Barchiesi ◽  
Robert Erra
Keyword(s):  
Random Number ◽  
Chaotic Maps ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

Trident, a New Pseudo Random Number Generator Based on Coupled Chaotic Maps

2010 ◽  
pp. 183-190 ◽  
Author(s):  
Amalia Beatriz Orúe López ◽  
Gonzalo Álvarez Marañon ◽  
Alberto Guerra Estévez ◽  
Gerardo Pastor Dégano ◽  
Miguel Romera García ◽  
...  
Keyword(s):  
Random Number ◽  
Chaotic Maps ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

Fuzzy Based Pseudo Random Number Generator used for Wireless Networks

2013 ◽  
Vol 16 (2) ◽  
pp. 210-216 ◽  
Author(s):  
Sattar B. Sadkhan ◽  
◽  
Sawsan K. Thamer ◽  
Najwan A. Hassan ◽  
◽  
...  
Keyword(s):  
Wireless Networks ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo 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.

Sign in / Sign up

Export Citation Format

Share Document