True pseudo-random number generation using chaotic maps
Generating a very high-quality random data is crucial for simulations using the Monte Carlo-method, secure cryptographic applications, and data security. There are two main methods in generating random data. The first method is called the hardware random number generator where it measures physical p...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/149455 |
| _version_ | 1811679684926111744 |
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| author | Teo, Jacob Wei Jie |
| author2 | Lin Rongming |
| author_facet | Lin Rongming Teo, Jacob Wei Jie |
| author_sort | Teo, Jacob Wei Jie |
| collection | NTU |
| description | Generating a very high-quality random data is crucial for simulations using the Monte Carlo-method, secure cryptographic applications, and data security. There are two main methods in generating random data. The first method is called the hardware random number generator where it measures physical phenomenon that are expected to be random such as atmospheric noise. However, they are limited by the number of random bits per second it can produce. The second method is called the pseudo-random number generator where it uses computational algorithm to generate long sequence of random data. Chaotic discrete dynamic systems such as logistic map have been used to generate pseudo-random number. However, chaos theory states that within the apparent randomness in a chaotic system, there are underlying patterns, repetition, and interconnectedness which are not desirable for most real-world applications. In order to further randomise the data and remove such order within apparent randomness, a new premium Pseudo-Random Number Generator based on Modulized Chaotic System Dynamics (PRNG-MCSD) is proposed. Modulo operation provides the strongest discontinuity and time-varying nonlinearity which generates very high-quality data through its repeated geometrical folding operations. The principle and the dynamic characteristics of the PRNG-MCSD would be discussed. Results based on statistical analyses such as Diehard and NIST test shows that the proposed PRNG-MCSD can generate very high-quality random data for simulations using the Monte Carlo-method, secure cryptographic applications, and data security. |
| first_indexed | 2024-10-01T03:13:05Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/149455 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:13:05Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1494552021-05-19T02:14:26Z True pseudo-random number generation using chaotic maps Teo, Jacob Wei Jie Lin Rongming School of Mechanical and Aerospace Engineering MRMLIN@ntu.edu.sg Engineering::Aeronautical engineering Generating a very high-quality random data is crucial for simulations using the Monte Carlo-method, secure cryptographic applications, and data security. There are two main methods in generating random data. The first method is called the hardware random number generator where it measures physical phenomenon that are expected to be random such as atmospheric noise. However, they are limited by the number of random bits per second it can produce. The second method is called the pseudo-random number generator where it uses computational algorithm to generate long sequence of random data. Chaotic discrete dynamic systems such as logistic map have been used to generate pseudo-random number. However, chaos theory states that within the apparent randomness in a chaotic system, there are underlying patterns, repetition, and interconnectedness which are not desirable for most real-world applications. In order to further randomise the data and remove such order within apparent randomness, a new premium Pseudo-Random Number Generator based on Modulized Chaotic System Dynamics (PRNG-MCSD) is proposed. Modulo operation provides the strongest discontinuity and time-varying nonlinearity which generates very high-quality data through its repeated geometrical folding operations. The principle and the dynamic characteristics of the PRNG-MCSD would be discussed. Results based on statistical analyses such as Diehard and NIST test shows that the proposed PRNG-MCSD can generate very high-quality random data for simulations using the Monte Carlo-method, secure cryptographic applications, and data security. Bachelor of Engineering (Aerospace Engineering) 2021-05-19T02:14:25Z 2021-05-19T02:14:25Z 2021 Final Year Project (FYP) Teo, J. W. J. (2021). True pseudo-random number generation using chaotic maps. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149455 https://hdl.handle.net/10356/149455 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Aeronautical engineering Teo, Jacob Wei Jie True pseudo-random number generation using chaotic maps |
| title | True pseudo-random number generation using chaotic maps |
| title_full | True pseudo-random number generation using chaotic maps |
| title_fullStr | True pseudo-random number generation using chaotic maps |
| title_full_unstemmed | True pseudo-random number generation using chaotic maps |
| title_short | True pseudo-random number generation using chaotic maps |
| title_sort | true pseudo random number generation using chaotic maps |
| topic | Engineering::Aeronautical engineering |
| url | https://hdl.handle.net/10356/149455 |
| work_keys_str_mv | AT teojacobweijie truepseudorandomnumbergenerationusingchaoticmaps |