• Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
No Downloads

Views

Total Views
457
On Slideshare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
5
Comments
0
Likes
1

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • According to APWG
    • According to PhishTank
    Total phishing attack. (Up to 6 th April 2010) Phishes Verified as Valid Suspected Phishes Submitted Total 531086 Total 928206 Online 2770 Online 3021 Offline 528316 Offline 925174
  • 7.
    • Social response
      • Educating people.
      • Changing habit.
    • Technical support
      • Identify phishing site.
      • Implementation of secure model.
      • Browser alert.
      • Eliminating phishing mails.
      • Monitoring and Takedown.
  • 8.  
  • 9.  
  • 10.  
  • 11.  
  • 12. Approach Accuracy Time (second) IP based URL 100% 17 Exists in phishing database 97% 59 Matching source content 81% 134 Abnormal condition 79% 51
  • 13.
    • 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.