A parallelizable chaos-based true random number generator based on mobile device cameras for the Android platform

Implementing a Chaotic Cryptosystem by Performing Parallel Computing on Embedded Systems with Multiprocessors

“…For purposes of comparison the entropy results to other related works that also report results using the Lena RGB image with 8-bit RGB format. Table 2 shows that the proposed method using the Tinkerbell map [ 73 ] presents better entropy results versus most related works reported by [ 4 , 11 , 25 , 32 , 36 , 59 , 77 , 81 ], except work [ 41 ], which reports the better entropy. Thus, confirming that the high arithmetic precision helps to improve the entropy of the encrypted information.…”

“…On the other hand, pseudo-random number generators (PRNGs) [ 4 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ], and truly random number generators (TRNGs) [ 41 , 42 , 43 , 44 , 45 ] are important modules in the development of cryptosystems to be robust against different types of security attacks. Some of these PRNGs and TRNGs have been implemented in personal computers and in embedded systems [ 29 , 30 , 31 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 ].…”

“…There are different types of parallel computing: bit-level parallelism, instruction level parallelism, data parallelism, and task parallelism. Parallelism has been employed for many years, especially in high-performance computing; however, interest in this field has grown lately due to the physical hardware that limits the increase of frequency of CPUs [ 41 , 59 , 74 , 75 ]. In addition, the consumption of energy and consequently the generation of heat from computers constitutes a focal point in the technological development of recent years [ 75 , 76 ].…”

“…From our knowledge and based on the reviewed literature, few works report the use of parallel computing for the encryption of information, see for example [ 15 , 41 , 44 , 59 , 77 , 78 , 79 , 80 , 81 , 82 ], but nevertheless, there are not any reported works in which profiling techniques and parallel computation are used for the encryption of high-resolution digital images using PRNGs on a cluster of embedded systems with multiprocessors. Except the work [ 41 ] reports a parallelizable chaos-based TRNG implemented on mobile device, but is not reported any implementation of parallel encryption on embedded system. Therefore, this paper proposes to use a different hardware from that commonly reported in the literature.…”

“…Additionally, the method reported by [ 73 ] is used for the encryption of information using multiple-precision arithmetic [ 83 ]. The Python programming language [ 84 ] is used to process several significant decimals higher than that reported in the works [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 16 , 17 , 18 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ] and which are based on the IEEE 754 standard [ 54 ], typically used in computers and FPGAs. It is important to emphasize that Python is a scientific programming language [ 84 ] with the following advantages: open-source, free license, an...…”