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TOWARDS DETECTING PHISHING WEB-PAGES Presented by, Md. Merazul Islam (0507036) & Shuvradeb Barman Srijon (0507044) Supervised by, Mr. Muhammad Sheikh Sadi Assistant Professor Department of Computer Science and Engineering Khulna University of  Engineering and Technology Khulna 9203, Bangladesh.
Introduction Cyber Crime- the major concern. Internet fraud affects the rapidly growing online services. E-commerce is the main target. Social communication sites and mail service are also attack of them. Technical steps needed to defend them.
Phishing? A criminal trick of stealing sensitive personal information. Fooled user and push them to fall in the trick. Use social engineering and technical strategy. Mainly, duplicate original web-pages. First describe in 1987.
Problem Statement Phishing attacks succeed if users fail to detect phishing sites. Previous anti-phishing falls into four categories: Study on phishing Training people User interface Detection tools Precious works deals with limited service. Our approach- Development of an automated phishing detection method.
Attributes of Phishing Similar appearance of web-page. IP based URL & Non Matching URL. URL contain abnormal characters. Mis-spelled URL. Using script or add-in to web browser to cover the address bar.
Phishing Stats According to APWG According to PhishTank Total phishing attack. (Up to 6th April 2010)
Anti-phishing Social response Educating people. Changing habit. Technical support Identify phishing site. Implementation of secure model. Browser alert. Eliminating phishing mails. Monitoring and Takedown.
Methodology
Methodology
Methodology
results
Experimental analysis
Discussion Our approach reduces the ability of attackers to automate their attacks, cutting into their profitability.  By using the minimal knowledge base provided by the user-selected web-page, our system is able to compare potential phishing sites with real sites. Performance and accuracy can be improved by using an image segmentation. Flash contents can’t be validated whether phishing threat or not in our system.
Thank You ?

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36 44 Final

  • 1. TOWARDS DETECTING PHISHING WEB-PAGES Presented by, Md. Merazul Islam (0507036) & Shuvradeb Barman Srijon (0507044) Supervised by, Mr. Muhammad Sheikh Sadi Assistant Professor Department of Computer Science and Engineering Khulna University of Engineering and Technology Khulna 9203, Bangladesh.
  • 2. Introduction Cyber Crime- the major concern. Internet fraud affects the rapidly growing online services. E-commerce is the main target. Social communication sites and mail service are also attack of them. Technical steps needed to defend them.
  • 3. Phishing? A criminal trick of stealing sensitive personal information. Fooled user and push them to fall in the trick. Use social engineering and technical strategy. Mainly, duplicate original web-pages. First describe in 1987.
  • 4. Problem Statement Phishing attacks succeed if users fail to detect phishing sites. Previous anti-phishing falls into four categories: Study on phishing Training people User interface Detection tools Precious works deals with limited service. Our approach- Development of an automated phishing detection method.
  • 5. Attributes of Phishing Similar appearance of web-page. IP based URL & Non Matching URL. URL contain abnormal characters. Mis-spelled URL. Using script or add-in to web browser to cover the address bar.
  • 6. Phishing Stats According to APWG According to PhishTank Total phishing attack. (Up to 6th April 2010)
  • 7. Anti-phishing Social response Educating people. Changing habit. Technical support Identify phishing site. Implementation of secure model. Browser alert. Eliminating phishing mails. Monitoring and Takedown.
  • 13. Discussion Our approach reduces the ability of attackers to automate their attacks, cutting into their profitability. By using the minimal knowledge base provided by the user-selected web-page, our system is able to compare potential phishing sites with real sites. Performance and accuracy can be improved by using an image segmentation. Flash contents can’t be validated whether phishing threat or not in our system.