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_aJoshua Janric A. Antonio, Emerson C. Roxas, John Kelly C. Temena.
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_aAn Enhancement of the Rail - Fence Cipher applied in an instant messaging app.
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_aunmediated
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_aUndergraduate Thesis : (Bachelor of Science in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2024.
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_aABSTRACT: This study establishes an enhanced Rail-Fence Cipher by addressing its limitations and improving its overall security. The Rail-Fence cipher is a simple transposition cipher that rearranges the plaintext's characters in a zig-zag patter to produce itw ciphertext. This simplicity of the cipher exhibits numerous problems within it, specifically its vulnerability to brute force attacks and low confusion and diffusion properties. These weaknesses leave the Rail-Fence cipher open to a plethora of exploitation that can jeopardize the confidentiality and integrity of sensitive data. To address the aforementioned weaknessesof the Rail-Fence cipher, the researchers employed innovative techniques such as adding randomized block sizes to add complexity to the algorithm, bit level implementation to increase its diffusion rates, and hybridization with a substitution cipher to increae its confusion rates. The proposed enhancement was then tested and compared with previous algorithms. The findings indicate that the enhanced Rail-Fence cipher outperforms both the traditional Rail-Fence cipher and existing enhancements in terms of resistance again st brute force attacks and achieving higher avalanche effect. It achieved an estimated time in milleniums of 2.14E+15 for a brute force attack to crack the ciphertext. . While the achieving an avalanche effect ranging from 37-38%. Additionally, the ciphertext generated by the enhanced Rail-Fence cipher exhibits a significantly higher variance from the plaintext, as demonstrated by frequency analysis. By addressing critical limitations of the traditional Rail-Fence cipher and integrating innovative techniques, this shows promise to the advancement of cybersecurity measures in an increasingly interconnected world.
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