Trustworthiness testing of phishing websites: A behavior model-based approach

نویسندگان

  • Hossain Shahriar
  • Mohammad Zulkernine
چکیده

Phishing attacks allure website users to visit fake web pages and provide their personal information. However, testing of phishing websites is challenging. Unlike traditional web-based program testing, we do not know the response of form submissions in advance. There exists lack of efforts to help anti-phishing professionals who manually verify a reported phishing site and take further actions. Moreover, current tools cannot detect phishing attacks that leverage vulnerabilities in trusted websites such as cross site scripting. An attackermight generate input forms by injecting script code and steal credentials. To address these challenges, we propose1 testing suspected phishing websites based on trustworthiness testing approach. In a trustworthiness testing, a website is not tested against a set of known inputs and matched the expected outputs with the actual ones. Rather, we check whether the behavior (response) of websites matches with our knowledge of phishing or legitimate website behaviors to decide whether a website is phishing or legitimate. We consider a suspected website as a web-based program and test the program based on a behavior model. The model is described using the notion of Finite State Machine (FSM) that captures the submission of forms with random inputs and the corresponding responses. We then identify a number of heuristics followed by a set of heuristic combination to assist a tester deciding whether websites are phishing or legitimate based on their up-to-date behaviors. We implement a tool named PhishTester to automate the testing process. We evaluate the proposed approach with both phishing and legitimate websites. The results show that the approach incurs zero false negatives and positives in detecting phishing and legitimate websites, respectively. Moreover, our approach can detect advanced XSS-based attacks that many contemporary tools currently fail to detect. © 2011 Elsevier B.V. All rights reserved.

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

Detecting Fake Websites Using Swarm Intelligence Mechanism in Human Learning

The internet and its various services have made users to easily communicate with each other. Internet benefits including online business and e-commerce. E-commerce has boosted online sales and online auction types. Despite their many uses and benefits, the internet and their services have various challenges, such as information theft, which challenges the use of these services. Information thef...

متن کامل

Intelligent Security for Phishing Online using Adaptive Neuro Fuzzy Systems

Anti-phishing detection solutions employed in industry use blacklist-based approaches to achieve low falsepositive rates, but blacklist approaches utilizes website URLs only. This study analyses and combines phishing emails and phishing web-forms in a single framework, which allows feature extraction and feature model construction. The outcome should classify between phishing, suspicious, legit...

متن کامل

A Novel Approach for Predicting Phishing Websites Using the Mapreduce Framework

In this paper, we have proposed a new approach named as " A Novel Approach for Predicting Phishing Websites using Map Reduce Framework " to overcome the difficulty and complexity in detecting and predicting phishing website. We proposed an efficient, resilient and effective approach that is based on using MapReduce framework, classification Data Mining algorithms and cluster methodology. Detect...

متن کامل

Intelligent Detection System for e-banking Phishing websites using Fuzzy Data Mining

Detecting and identifying e-banking Phishing websites is really a complex and dynamic problem involving many factors and criteria. Because of the subjective considerations and the ambiguities involved in the detection, Fuzzy Data Mining Techniques can be an effective tool in assessing and identifying e-banking phishing websites since it offers a more natural way of dealing with quality factors ...

متن کامل

A Hybrid Approach to Detect Zero Day Phishing Websites

Phishing is a significant problem that tricks unsuspecting users into revealing private information involving fraudulent email and websites. This causes tremendous economic loss every year. In this paper, we proposed a novel hybrid phish detection method based on phishing blacklists and phishing properties. We used some fresh phish from PhishTank that were recently added to test that it can be ...

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:
  • Future Generation Comp. Syst.

دوره 28  شماره 

صفحات  -

تاریخ انتشار 2012