Development of a Quantum-Based Algorithm for Cybersecurity in Bayero University, Kano, Kano State
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- NGN 5000
Background of the Study
With the rapid digitalization of educational processes, Bayero University, Kano, faces increasing cybersecurity challenges. The growing volume of online learning platforms, research databases, and digital administrative systems increases the potential for cyber-attacks, data breaches, and system intrusions. Traditional cybersecurity algorithms, based on classical computation, are becoming less effective against the evolving landscape of cyber threats. Quantum computing, with its ability to process vast amounts of data simultaneously, offers an innovative solution to enhance cybersecurity measures (Farhi et al., 2023). Quantum-based algorithms, such as those utilizing Shor’s and Grover’s algorithms, can provide more efficient ways of detecting, preventing, and mitigating cyber-attacks compared to traditional methods (Childs et al., 2024).
The development of a quantum-based cybersecurity algorithm tailored to the needs of Bayero University, Kano, could strengthen the university’s defense mechanisms, enabling it to better protect sensitive student data, research materials, and institutional communications from cyber threats. This research aims to create a quantum-based algorithm that could be integrated into the university's existing cybersecurity infrastructure to improve data protection and incident response capabilities.
Statement of the Problem
Bayero University, Kano, faces significant cybersecurity challenges due to the increasing frequency and sophistication of cyber-attacks targeting educational institutions. Existing cybersecurity algorithms based on classical computing methods have proven inadequate in providing comprehensive protection against modern cyber threats, such as data breaches and ransomware attacks. The university requires an advanced solution to strengthen its cybersecurity framework, specifically a quantum-based algorithm that can improve the detection and prevention of such threats.
Objectives of the Study
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To develop a quantum-based algorithm for enhancing cybersecurity at Bayero University, Kano.
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To assess the effectiveness of the quantum-based algorithm in detecting and mitigating cyber threats at the university.
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To integrate the quantum-based algorithm into the university’s existing cybersecurity infrastructure and evaluate its impact.
Research Questions
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How can a quantum-based algorithm be developed to improve cybersecurity at Bayero University, Kano?
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How effective is the quantum-based algorithm in detecting and preventing cyber-attacks at the university?
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What are the challenges and benefits of integrating the quantum-based algorithm into the university’s cybersecurity infrastructure?
Significance of the Study
The findings of this study will contribute to the advancement of cybersecurity solutions in academic institutions, particularly in regions where the increasing threat of cyber-attacks requires novel and advanced approaches. By developing a quantum-based algorithm for Bayero University, Kano, the study will enhance the university’s ability to protect sensitive data and improve its overall cybersecurity resilience.
Scope and Limitations of the Study
The study will focus on the development and assessment of a quantum-based cybersecurity algorithm tailored for Bayero University, Kano, located in Kano State. The research will specifically address the algorithm’s effectiveness in mitigating cyber threats but will not explore broader cybersecurity policy or infrastructural issues.
Definitions of Terms
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Quantum Computing: A field of computing that leverages the principles of quantum mechanics to perform computations at a significantly higher speed and efficiency than classical computing.
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Cybersecurity Algorithm: A set of computational rules and procedures designed to protect computer systems and networks from cyber threats.
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Quantum-Based Algorithm: An algorithm that utilizes quantum computing principles to solve problems, often achieving faster or more efficient results than classical algorithms.
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