Investigation into the Effectiveness of Email Phishing Detection Systems in Federal University, Gashua, Yobe State
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
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- NGN 5000
Background of the Study
Phishing attacks are one of the most prevalent types of cyber threats targeting university networks. These attacks typically involve tricking users into revealing sensitive information such as usernames, passwords, or financial data by disguising malicious emails as legitimate communications. Federal University, Gashua, Yobe State, like other educational institutions, faces significant challenges in protecting its network from email phishing threats, which can lead to data breaches, financial loss, and reputational damage.
Email phishing detection systems (EPDS) are designed to detect and filter phishing attempts before they reach users’ inboxes. These systems rely on various techniques, including machine learning algorithms, heuristic analysis, and blacklists, to identify phishing emails. This study aims to evaluate the effectiveness of the email phishing detection systems currently in use at Federal University, Gashua, and determine how well they protect users from phishing attacks.
Statement of the Problem
Despite the presence of email phishing detection systems, phishing attacks remain a significant threat to campus networks. The existing detection systems at Federal University, Gashua, may not be fully effective in preventing phishing attacks, which can compromise user credentials and sensitive university data. This study will investigate the effectiveness of the current phishing detection systems and identify potential improvements.
Objectives of the Study
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To evaluate the performance of email phishing detection systems currently deployed at Federal University, Gashua.
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To identify the limitations and challenges associated with existing phishing detection systems.
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To recommend strategies for enhancing the effectiveness of email phishing detection systems at the university.
Research Questions
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How effective are the current email phishing detection systems at Federal University, Gashua?
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What are the limitations of existing phishing detection systems in identifying phishing emails?
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How can the email phishing detection systems be improved to better protect university users from phishing attacks?
Significance of the Study
This study will help Federal University, Gashua, to assess and enhance its email phishing detection capabilities, thereby reducing the risks associated with phishing attacks. The findings could inform policy and technology upgrades that will better protect students, faculty, and staff from cyber threats.
Scope and Limitations of the Study
The study will focus specifically on evaluating email phishing detection systems at Federal University, Gashua. It will not address phishing threats from other communication channels or network security measures beyond email.
Definitions of Terms
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Phishing: A type of cyberattack where attackers impersonate legitimate entities to deceive individuals into revealing sensitive information.
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Email Phishing Detection System (EPDS): A system designed to identify and block phishing emails before they reach users' inboxes.
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Machine Learning Algorithms: A subset of artificial intelligence that enables systems to learn patterns and make predictions or decisions based on data.
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