Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/21628
Title: Performance Evaluation of Blowfish Encryption Algorithm
Other Titles: تقييم أداء خوارزمية بلوفش للتشفير
Authors: Elshaikh, Mohaned Abduallah
Supervisor, - Faisal Mohammed Abdallah
Keywords: Evaluation of Blowfish
Encryption Algorithm
Issue Date: 1-Oct-2017
Publisher: Sudan University of Science & Technology
Citation: Elshaikh, Mohaned Abduallah.Performance Evaluation of Blowfish Encryption Algorithm\Mohaned Abduallah Elshaikh;Faisal Mohammed Abdallah.-Khartoum:Sudan University of Science & Technology,College of Computer Science and Information Technology,2017.-61p.:ill.;28cm.-M.Sc.
Abstract: The revolution and improvement of life in terms of technologies, allow users to share their data and information and this is the one of common uses of computer technologies. But with world full of third parties, who is capable of collect, theft and destroy information of others without any authority, and cryptography is method was developed to help users to keep their information secure using different algorithms. Blowfish is a cipher algorithm and it is simple, secure and efficient, and the performance of blowfish effected by the size of message and key length. The research aims to evaluate the performance of Blowfish by modifying the structure of F function. The modified Blowfish will use just two S-box in F function instead of four that used in Blowfish to compare encryption time and security. Encryption time and decryption time were calculated to compare between Blowfish and modified Blowfish and results state that the modified Blowfish is better in term of performance. The results ofDiehard Batterythat used to test the randomness shows that Blowfish algorithmis in high level security more that modified Blowfish, so is better to use Blowfish algorithm to encrypt data and applications that need a high level of security
Description: Thesis
URI: http://repository.sustech.edu/handle/123456789/21628
Appears in Collections:Masters Dissertations : Computer Science and Information Technology

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