Introduction
The advancement of technology has brought about a significant increase in cyber threats, with phishing attacks being one of the most common forms of cybercrime. Phishing attacks are designed to deceive individuals into divulging sensitive information such as login credentials, financial details, and personal information. Traditional phishing detection methods have proven to be insufficient in combating these attacks, leading to the development of AI-powered phishing detection tools.
This thesis aims to explore the effectiveness of AI-powered phishing detection tools in detecting and preventing phishing attacks. The study will examine the current landscape of phishing attacks, the limitations of traditional detection methods, and the potential benefits of utilizing AI technology for phishing detection. By evaluating the performance of AI-powered tools, this research seeks to provide insights into the strengths and weaknesses of these tools in combating phishing attacks.
Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms
Chapter 2: Literature Review
2.1 Overview of phishing attacks
2.2 Traditional phishing detection methods
2.3 Evolution of AI-powered phishing detection tools
2.4 Benefits of AI technology in phishing detection
2.5 Challenges of AI-powered phishing detection tools
2.6 Case studies of AI-powered phishing detection tools
2.7 Comparison of AI-powered tools with traditional methods
2.8 Current trends in phishing attacks
2.9 Ethical considerations in AI-powered phishing detection
2.10 Future directions in AI-powered phishing detection research
Chapter 3: Research Methodology
3.1 Research design
3.2 Data collection methods
3.3 Sampling techniques
3.4 Data analysis procedures
3.5 Validity and reliability of research findings
3.6 Ethical considerations
3.7 Pilot testing
3.8 Limitations of the research methodology
Chapter 4: Discussion of Findings
4.1 Overview of research findings
4.2 Performance evaluation of AI-powered phishing detection tools
4.3 Comparison of different AI algorithms in phishing detection
4.4 User perceptions and acceptance of AI-powered tools
4.5 Practical implications of the research findings
4.6 Recommendations for future research
4.7 Implications for cybersecurity practices
4.8 Limitations of the study
4.9 Conclusion
Chapter 5: Conclusion and Summary
5.1 Summary of key findings
5.2 Contributions to the field of cybersecurity
5.3 Implications for practitioners
5.4 Recommendations for policymakers
5.5 Future research directions
5.6 Conclusion
Thesis Overview: The effectiveness of AI-powered phishing detection tools
Phishing attacks have become a significant threat to individuals and organizations, with cybercriminals constantly evolving their tactics to deceive unsuspecting victims. Traditional phishing detection methods have struggled to keep pace with these evolving threats, leading to the development of AI-powered tools as a potential solution. This thesis aims to investigate the effectiveness of AI-powered phishing detection tools in combating phishing attacks, by evaluating their performance, benefits, challenges, and comparing them with traditional detection methods. The research methodology involves a comprehensive literature review, data collection, analysis, and discussion of findings to provide valuable insights into the strengths and weaknesses of AI-powered tools. The study concludes with recommendations for practitioners, policymakers, and future research directions in the field of cybersecurity.
