AN ANTI PHISHING STRATEGY BASED ON VISUAL SIMILARITY ASSESSMENT


ABSTRACT
Anti-phishing strategy uses visual characteristics to identify potential phishing sites and measure suspicious pages similarity to actual sites registered with the system. The first of two sequential processes in the SiteWatcher system runs on local email servers and monitors emails for keywords and suspicious URLs. The second process then compares the potential phishing pages against actual pages and assesses visual similarities between them in terms of key regions, page layouts, and overall styles. The approach is designed to be part of an enterprise anti-phishing solution.


TABLE OF CONTENT
TITLE PAGE                                   
CERTIFICATION                               
APPROVAL                               
DEDICATION                                   
ACKNOWLEDGEMENT                       
ABSTRACT                                   
TABLE OF CONTENT               
                
CHAPTER ONE
1.0    INTRODUCTION                           
1.1    STATEMENT OF PROBLEM                       
1.2    PURPOSE OF STUDY                           
1.3    AIMS AND OBJECTIVES                        
1.4    SCOPE/DELIMITATIONS                       
1.5    LIMITATIONS/CONSTRAINTS                       
1.6    DEFINITION OF TERMS 
                      
CHAPTER TWO
2.0    LITERATURE REVIEW        
                   
CHAPTER THREE
3.0    METHODS FOR FACT FINDING AND DETAILED DISCUSSIONS OF THE SYSTEM
3.1     METHODOLOGIES FOR FACT-FINDING
3.2    DISCUSSIONS       
     
CHAPTER FOUR
4.0    FUTURES, IMPLICATIONS AND CHALLENGES OF THE SYSTEM
4.1    FUTURES
4.2    IMPLICATIONS
4.3    CHALLENGES

CHAPTER FIVE
5.0    RECOMMENDATIONS, SUMMARY AND CONCLUSION       
5.1    RECOMMENDATION                           
5.2    SUMMARY                               
5.3    CONCLUSION                               
5.4    REFERENCES                       

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APA

LB3KrQR5c0006fde3c696.03592209, X. (2018). AN ANTI PHISHING STRATEGY BASED ON VISUAL SIMILARITY ASSESSMENT. Afribary. Retrieved from https://beta.afribary.com/works/an-anti-phishing-strategy-based-on-visual-similarity-assessment-6416

MLA 8th

LB3KrQR5c0006fde3c696.03592209, XuZJAx35c0006fde31d75.71658929 "AN ANTI PHISHING STRATEGY BASED ON VISUAL SIMILARITY ASSESSMENT" Afribary. Afribary, 29 Jan. 2018, https://beta.afribary.com/works/an-anti-phishing-strategy-based-on-visual-similarity-assessment-6416. Accessed 24 Apr. 2025.

MLA7

LB3KrQR5c0006fde3c696.03592209, XuZJAx35c0006fde31d75.71658929 . "AN ANTI PHISHING STRATEGY BASED ON VISUAL SIMILARITY ASSESSMENT". Afribary, Afribary, 29 Jan. 2018. Web. 24 Apr. 2025. < https://beta.afribary.com/works/an-anti-phishing-strategy-based-on-visual-similarity-assessment-6416 >.

Chicago

LB3KrQR5c0006fde3c696.03592209, XuZJAx35c0006fde31d75.71658929 . "AN ANTI PHISHING STRATEGY BASED ON VISUAL SIMILARITY ASSESSMENT" Afribary (2018). Accessed April 24, 2025. https://beta.afribary.com/works/an-anti-phishing-strategy-based-on-visual-similarity-assessment-6416