THE ROLE OF ARTIFICIAL INTELLIGENCE-DRIVEN PHISHING DETECTION IN NIGERIAN COMPANIES: A CASE STUDY OF IT FIRMS IN ABUJA, FCT
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- Table of Content: Available
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- NGN 5000
CHAPTER ONE
1.1 Background of the Study
Cybersecurity threats, including phishing attacks, are a growing concern for organizations worldwide. Phishing involves the use of deceptive emails or websites to steal sensitive information such as passwords, financial data, and intellectual property. Nigerian companies, particularly IT firms, are prime targets due to their reliance on digital systems and sensitive client data.
Artificial Intelligence (AI)-driven phishing detection systems offer a proactive solution to this challenge. These systems use machine learning algorithms to identify phishing patterns, analyze email content, and detect anomalies in real-time. Unlike traditional methods, AI systems are adaptive and can respond to emerging phishing techniques, making them more effective in safeguarding digital assets.
In Abuja, IT firms are at the forefront of digital innovation, but they remain vulnerable to phishing attacks. This study examines the role of AI-driven phishing detection systems in protecting IT firms in Abuja, focusing on their effectiveness, challenges, and impact.
1.2 Statement of the Problem
Despite advancements in cybersecurity, IT firms in Abuja face persistent phishing threats that compromise sensitive data and disrupt operations. Traditional detection methods are often insufficient for countering sophisticated phishing attacks. This study investigates how AI-driven phishing detection systems can address these challenges.
1.3 Aim and Objectives of the Study
The aim of this study is to evaluate the role of AI-driven phishing detection in protecting IT firms in Abuja. The specific objectives are:
- To assess the effectiveness of AI-driven systems in detecting and preventing phishing attacks.
- To identify challenges faced by IT firms in implementing AI-driven phishing detection.
- To analyze the impact of AI phishing detection systems on cybersecurity outcomes.
1.4 Research Questions
- How effective are AI-driven phishing detection systems in protecting IT firms in Abuja?
- What challenges do IT firms face in adopting AI-driven phishing detection systems?
1.5 Research Hypotheses
- AI-driven phishing detection systems significantly reduce phishing attack incidents.
- The adoption of AI-driven phishing detection enhances data security in IT firms.
- High implementation costs limit the adoption of AI phishing detection systems.
1.6 Significance of the Study
This study provides insights into the role of AI in combating phishing attacks, offering recommendations for improving cybersecurity strategies in Nigerian IT firms. It contributes to the broader discourse on AI’s application in cybersecurity.
1.7 Scope and Limitation of the Study
The study focuses on IT firms in Abuja and their use of AI-driven phishing detection systems. It excludes other cybersecurity threats and companies outside the IT sector. Limitations include access to proprietary security systems and data.
1.8 Definition of Terms
- Artificial Intelligence (AI): Systems that simulate human intelligence for tasks such as threat detection.
- Phishing: A cyberattack technique used to steal sensitive information through deceptive means.
- IT Firms: Companies specializing in information technology services and solutions.
- Abuja, FCT: The Federal Capital Territory of Nigeria and the study’s focus area.
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