PhishGuru: A System for Educating Users about Semantic Attacks

نویسندگان

  • Ponnurangam Kumaraguru
  • Jason Hong
  • Vincent Aleven
  • Rahul Tongia
  • Alessandro Acquisti
چکیده

Online security attacks are a growing concern among Internet users. Currently, the Internet community is facing three types of security attacks: physical, syntactic, and semantic. Semantic attacks take advantage of the way humans interact with computers or interpret messages. There are three major approaches to countering semantic attacks: silently eliminating the attacks, warning users about the attacks, and training users not to fall for the attacks. The existing methods for silently eliminating the attack and warning users about the attack are unlikely to perform flawlessly; furthermore, users are the weakest link in these attacks, it is essential that user training complement other methods. Most existing online training methodologies are less successful because: (1) organizations that create and host training materials expect users to proactively seek out such material themselves; (2) these organizations expect users to have some knowledge about semantic attacks; and (3) the training materials have not been designed with learning science principles in mind. The goal of this thesis is to show that computer users trained with an embedded training system – one grounded in the principles of learning science – are able to make more accurate online trust decisions than users who read traditional security training materials, which are distributed via email or posted online. To achieve this goal, we focus on “phishing,” a type of semantic attack. We have developed a system called “PhishGuru” based on embedded training methodology and learning science principles. Embedded training is a methodology in which training materials are integrated into the primary tasks users perform in their day–to–day lives. In contrast to existing training methodologies, the PhishGuru shows training materials to users through emails at the moment (“teachable moment”) users actually fall for phishing attacks. We evaluated the embedded training methodology through laboratory and field studies. Realworld experiments showed that people trained with PhishGuru retain knowledge even after 28 days. PhishGuru training does not decrease users’ willingness to click on links in legitimate messages. PhishGuru is also being used in a real-world implementation of the Anti-Phishing Working Group Landing Page initiative. The design principles established in this thesis will help researchers develop systems that can train users in other risky online situations. Dream, Dream, Dream! Dreams transform into thoughts and thoughts into actions. ∼ Dr. A. P. J. Abdul Kalam, Former President of India

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Testing PhishGuru in the Real World

In real world testing of PhishGuru, an embedded training system that teaches people how to protect themselves from phishing attacks, we found (a) PhishGuru is effective in training people in the real world; (b) users retained knowledge when trained with PhishGuru in the real world; (c) a large percentage of people who clicked on links in simulated emails proceeded to give some form of personal ...

متن کامل

School of Phish: A Real-Word Evaluation of Anti-Phishing Training (CMU-CyLab-09-002)

PhishGuru is an embedded training system that teaches users to avoid falling for phishing attacks by delivering a training message when the user clicks on the URL in a simulated phishing email. In previous lab and real-world experiments, we validated the effectiveness of this approach. Here, we extend our previous work with a 515-participant, real-world study in which we focus on long-term rete...

متن کامل

School of Phish: A Real-World Evaluation of Anti-Phishing Training

PhishGuru is an embedded training system that teaches users to avoid falling for phishing attacks by delivering a training message when the user clicks on the URL in a simulated phishing email. In previous lab and real-world experiments, we validated the effectiveness of this approach. Here, we extend our previous work with a 515-participant, real-world study in which we focus on long-term rete...

متن کامل

Analysis of User query refinement behavior based on semantic features: user log analysis of Ganj database (IranDoc)

Background and Aim: Information systems cannot be well designed or developed without a clear understanding of needs of users, manner of their information seeking and evaluating. This research has been designed to analyze the Ganj (Iranian research institute of science and technology database) users’ query refinement behaviors via log analysis.    Methods: The method of this research is log anal...

متن کامل

Use of Semantic Similarity and Web Usage Mining to Alleviate the Drawbacks of User-Based Collaborative Filtering Recommender Systems

  One of the most famous methods for recommendation is user-based Collaborative Filtering (CF). This system compares active user’s items rating with historical rating records of other users to find similar users and recommending items which seems interesting to these similar users and have not been rated by the active user. As a way of computing recommendations, the ultimate goal of the user-ba...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009