1.   مشاوره و انجام پروپوزال  و پایان نامه ، مشاوره در زمینه ارائه سمینار، 
       مشاوره و انجام مقاله های بین المللی و داخلی، 
       مشاوره و انجام مقاله در مجله های علمی پژوهشی معتبر، 
        مشاوره و آموزش شبیه سازی شبکه توسط شبیه ساز آکادمیک 2-NS، 
         مشاوره و آموزش شبیه سازهای ترافیک شهری از قبیل  SUMO، ONE، و ...
          کمک به دانشجویان برای پیاده سازی ایده ها و مقالات خود با شبیه سازهای
               NS2, NS3 , OMNET++ , ONE
     
    
                 شماره تماس :
                         حسین رنجبران:    09101607834   
                                          
    
                  ساعات تماس: 
                                      ۸ الی ۲۰
                         
                   ایمیل:
                         hossein.ranjbaran.it@gmail.com
                        
           
    

PhishLimiter: A Phishing Detection and Mitigation Approach Using Software-Defined Networking

شروع موضوع توسط AdMiN ‏28/6/18 در انجمن SDN

وضعیت موضوع:
You must be a logged-in, registered member of this site to view further posts in this thread.
  1. Administrator
    AdMiN
    هیات مدیره
    تاریخ عضویت:
    ‏3/10/13
    ارسال ها:
    2,191
    تشکر شده:
    316
    Phishing is one of the most harmful social engineering techniques to subdue end users where threat actors find a chance to gain access to critical information systems. A common approach in phishing is through the use of e-mail communication with an embedded hyperlink. The detection and mitigation of phishing attacks is a grand challenge due to the complexity of current phishing attacks. Existing techniques are often too time-consuming to be used in the real world in terms of detection and mitigation time. Likewise, they employ static detection rules that are not effective in the real world due to the dynamics of phishing attacks. In this paper, we present PhishLimiter, a new detection and mitigation approach, where we first propose a new technique for Deep Packet Inspection (DPI) and then leverage it with Software-Defined Networking (SDN) to identify phishing activities through e-mail and webbased communication. The proposed DPI approach consists of two components, phishing signature classification and real-time DPI. Based on the programmability of SDN, we develop Store and Forward (SF) mode and the Forward and Inspect (FI) mode to direct network traffic by using an Artificial Neural Network (ANN) model to classify phishing attack signatures and design the real-time DPI so that PhishLimiter can flexibly address the dynamics of phishing attacks in the real world. PhishLimiter also provides better network traffic management for containing phishing attacks since it has the global view of a network through SDN. Furthermore, we evaluate PhishLimiter using a real-world testbed environment and datasets consisting of real-world email with embedded links. Our extensive experimental study shows that PhishLimiter provides an effective and efficient solution to deter malicious activities.​
    لینک دانلود در پست بعد برای اعضاء قابل مشاهده است.
     
وضعیت موضوع:
You must be a logged-in, registered member of this site to view further posts in this thread.

این صفحه را به اشتراک بگذارید