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035 a| (Sirsi) o1371248848;

035 a| (OCoLC)1371248848;

049 a| EREE;

090 a| QA76.9.A25;

100 1 a| Leggett, Hunter W.,e| author.?| UNAUTHORIZED;

245 10 a| Genetic algorithm stream cipher key generation using NIST functions /c| by Hunter W. Leggett.;

264 1 a| [Greenville, N.C.] :b| [East Carolina University],c| 2022.;

300 a| 1 online resource (106 pages) :b| illustrations (some color);

336 a| textb| txt2| rdacontent;

337 a| computerb| c2| rdamedia;

338 a| online resourceb| cr2| rdacarrier;

347 a| text fileb| PDFc| 1.278 MB2| rda;

538 a| System requirements: Adobe Reader.;

538 a| Mode of access: World Wide Web.;

502 b| M.S.c| East Carolina Universityd| 2022.;

500 a| Presented to the Faculty of the Department of Technology Systems;

500 a| Advisor: Te-Shun Chou;

500 a| Title from PDF t.p. (viewed May 2, 2024).;

520 3 a| Stream ciphers are beneficial because of their efficiency, speed, and low resource utilization. However, stream ciphers are vulnerable to many attacks if they do not use strong keys for encryption and decryption. Thus, one way to increase the security of stream ciphers is to improve the key generation algorithm. This study sought to evaluate the keys produced by a genetic algorithm stream cipher when individual and combinations of fitness functions are used. Furthermore, this study identified which fitness function is the best for a specific scenario. For the genetic algorithm, the fitness tests are thirteen of the tests defined in NIST SP 800-22rla. The thirteen different fitness functions were inputted into the genetic algorithm stream cipher one at a time. Next, 50 total keys of varying bit sizes were generated. These keys were evaluated by using the Hamming distance between the keys and time that it took for key generation. After each individual fitness function was evaluated, two combinations of five tests were created and used as a single fitness function. The two combinations were the best performing NIST functions for Hamming distance and time for 256-bit keys. Sensitivity analysis was then performed to find the best possible combination of the NIST functions. Based on the results, using different individual functions or a combination of functions as a fitness functions changed the Hamming distance between the keys and the time that it takes to generate a key. Furthermore, using sensitivity analysis results for the top two, three, four, and five combinations for Hamming distance and time, prediction equations were created and used to predict values for other combinations and key sizes.;

504 a| Includes bibliographical references.;

650 0 a| Stream ciphers.=| ^A1172540;

650 0 a| Genetic algorithms.=| ^A313049;

650 0 a| Computer security.=| ^A257308;

653 a| Cryptography;

653 a| Hamming distance;

700 1 a| Chou, Te-Shun,d| 1964-e| degree supervisor.=| ^A1082236;

710 2 a| East Carolina University.b| Department of Technology Systems.?| UNAUTHORIZED;

856 40 z| Access via ScholarShipu| http://hdl.handle.net/10342/12298;

949 o| wjh;

994 a| C0b| ERE;

596 a| 1 4;

998 a| 5961418;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5961418-1001l| JNETm| JOYNERr| Ys| Yt| JNE3ETDu| 3/1/2023x| ETDz| JERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5961418-2001l| HSLELECm| HSLr| Ys| Yt| HEETDu| 3/1/2023x| ETDz| HERESOURCE;

Genetic algorithm stream cipher key generation using NIST functions / by Hunter W. Leggett.

Author/creator	Leggett, Hunter W. author.
Other author	Chou, Te-Shun, 1964- degree supervisor.
Other author	East Carolina University. Department of Technology Systems.
Format	Theses and dissertations
Publication	[Greenville, N.C.] : [East Carolina University], 2022.
Description	1 online resource (106 pages) : illustrations (some color)
Supplemental Content	Access via ScholarShip
Subjects	Stream ciphers. Genetic algorithms. Computer security.

Summary	Stream ciphers are beneficial because of their efficiency, speed, and low resource utilization. However, stream ciphers are vulnerable to many attacks if they do not use strong keys for encryption and decryption. Thus, one way to increase the security of stream ciphers is to improve the key generation algorithm. This study sought to evaluate the keys produced by a genetic algorithm stream cipher when individual and combinations of fitness functions are used. Furthermore, this study identified which fitness function is the best for a specific scenario. For the genetic algorithm, the fitness tests are thirteen of the tests defined in NIST SP 800-22rla. The thirteen different fitness functions were inputted into the genetic algorithm stream cipher one at a time. Next, 50 total keys of varying bit sizes were generated. These keys were evaluated by using the Hamming distance between the keys and time that it took for key generation. After each individual fitness function was evaluated, two combinations of five tests were created and used as a single fitness function. The two combinations were the best performing NIST functions for Hamming distance and time for 256-bit keys. Sensitivity analysis was then performed to find the best possible combination of the NIST functions. Based on the results, using different individual functions or a combination of functions as a fitness functions changed the Hamming distance between the keys and the time that it takes to generate a key. Furthermore, using sensitivity analysis results for the top two, three, four, and five combinations for Hamming distance and time, prediction equations were created and used to predict values for other combinations and key sizes.
General note	Presented to the Faculty of the Department of Technology Systems
General note	Advisor: Te-Shun Chou
General note	Title from PDF t.p. (viewed May 2, 2024).
Dissertation note	M.S. East Carolina University 2022.
Bibliography note	Includes bibliographical references.
Technical details	System requirements: Adobe Reader.
Technical details	Mode of access: World Wide Web.

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