Undergraduate proposal thesis for the College of Information Systems and Technology Management

By: Alcoriza, Marc Vincent C.; Ang, Lamuel Bien C
Language: English Publisher: . . c2025Description: Undergraduate Thesis: (Bachelor of Science in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2025Content type: text Media type: unmediated Carrier type: volumeGenre/Form: academic writingDDC classification: . LOC classification: QA76.9 A43 A43 2025
Contents:
ABSTRACT: This study focuses on enhancing the Obaida-Salman-Zugair Improved MDS Algorithm to ensure robust data integrity checking in school enrollment systems. Traditional MD5, while widely used for its simplicity and speed, is vulnerable to collision attacks, where different inputs produce the same hash output, compromising data security. The Obaida-Salman-Zugair Improved MD5 Algorithm was developed to address these vulnerabilities by introducing additional cryptographic layers, such as linear-feedback shift registers (LFSR) and XOR operations, to increase complexity and security. However, the algorithm still faces challenges in key generation efficiency, memory usage, and resistance to sophisticated cryptographic attacks. This research proposes an enhanced version of the Obaida-Salman-Zugair Improved MD5 Algorithm, tailored specifically for school enrollment systems. The enhancements include simplifying the key generation process by replacing LFSR with SHA-256 hashing and multiple salting stages, optimizing block processing through dynamic block size allocation, and strengthening security with salt-based entropy expansion, XOR-AND logic, and key stretching techniques like PBKDF2. These improvements aim to balance security and efficiency, ensuring real-time data processing while maintaining high resistance to attacks such as brute force, known-plaintext, and collision attacks. The study evaluates the proposed algorithm through simulations and comparative analyses, focusing on key generation time, memory efficiency, and entropy levels. Results indicate that the enhanced algorithm significantly reduces key generation time, minimizes memory waste, and improves entropy, making it more secure and scalable for handling various file sizes. The proposed algorithm demonstrates a 100% reduction in key generation time compared to the original Obaida-Salman-Zugair algorithm, with dynamic block processing reducing memory waste by up to 97% for smaller files. Additionally, the enhanced algorithm achieves higher entropy values, indicating resistance to cryptographic attack
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ABSTRACT: This study focuses on enhancing the Obaida-Salman-Zugair Improved MDS Algorithm to ensure robust data integrity checking in school enrollment systems. Traditional MD5, while widely used for its simplicity and speed, is vulnerable to collision attacks, where different inputs produce the same hash output, compromising data security. The Obaida-Salman-Zugair Improved MD5 Algorithm was developed to address these vulnerabilities by introducing additional cryptographic layers, such as linear-feedback shift registers (LFSR) and XOR operations, to increase complexity and security. However, the algorithm still faces challenges in key generation efficiency, memory usage, and resistance to sophisticated cryptographic attacks. This research proposes an enhanced version of the Obaida-Salman-Zugair Improved MD5 Algorithm, tailored specifically for school enrollment systems. The enhancements include simplifying the key generation process by replacing LFSR with SHA-256 hashing and multiple salting stages, optimizing block processing through dynamic block size allocation, and strengthening security with salt-based entropy expansion, XOR-AND logic, and key stretching techniques like PBKDF2. These improvements aim to balance security and efficiency, ensuring real-time data processing while maintaining high resistance to attacks such as brute force, known-plaintext, and collision attacks. The study evaluates the proposed algorithm through simulations and comparative analyses, focusing on key generation time, memory efficiency, and entropy levels. Results indicate that the enhanced algorithm significantly reduces key generation time, minimizes memory waste, and improves entropy, making it more secure and scalable for handling various file sizes. The proposed algorithm demonstrates a 100% reduction in key generation time compared to the original Obaida-Salman-Zugair algorithm, with dynamic block processing reducing memory waste by up to 97% for smaller files. Additionally, the enhanced algorithm achieves higher entropy values, indicating resistance to cryptographic attack

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