36 44 Final
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36 44 Final

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Transcript

  • 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.
  • 8. Methodology
  • 9. Methodology
  • 10. Methodology
  • 11. results
  • 12. Experimental analysis
  • 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.
  • 14. Thank You
    ?