Phishing Detection via Identification of Website Identity

Chang, Ee Hung; Chiew, Kang Leng; Sze, San Nah; Tiong, Wei King

doi:10.1109/icitcs.2013.6717870

Cited by 46 publications

(14 citation statements)

References 6 publications

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“…Similarly, extracting the logo from a webpage screenshot and using it in Google Image Search leads to identify the target of 87.0% of phishs in [41]. HREF links have been used to build community graphs of webpages.…”

Section: Related Workmentioning

confidence: 99%

Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application

Marchal

Armano²,

Gröndahl

et al. 2017

IEEE Trans. Comput.

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Abstract-Phishing is a major problem on the Web. Despite the significant attention it has received over the years, there has been no definitive solution. While the state-of-the-art solutions have reasonably good performance, they suffer from several drawbacks including potential to compromise user privacy, difficulty of detecting phishing websites whose content change dynamically, and reliance on features that are too dependent on the training data. To address these limitations we present a new approach for detecting phishing webpages in real-time as they are visited by a browser. It relies on modeling inherent phisher limitations stemming from the constraints they face while building a webpage. Consequently, the implementation of our approach, Off-the-Hook, exhibits several notable properties including high accuracy, brand-independence and good language-independence, speed of decision, resilience to dynamic phish and resilience to evolution in phishing techniques. Off-the-Hook is implemented as a fully-client-side browser add-on, which preserves user privacy. In addition, Off-the-Hook identifies the target website that a phishing webpage is attempting to mimic and includes this target in its warning. We evaluated Off-the-Hook in two different user studies. Our results show that users prefer Off-the-Hook warnings to Firefox warnings.

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Section: Related Workmentioning

confidence: 99%

Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application

Marchal

Armano²,

Gröndahl

et al. 2017

IEEE Trans. Comput.

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show abstract

“…In this paper, we propose a method that belongs to the heuristic-based approach, and it is an extension of our work proposed in Chang et al (2013). We claim that in order to detect a phishing website, we must first be able to determine the consistency of the website identity.…”

Section: Introductionmentioning

confidence: 96%

“…As we all know, the relationship between a logo and the domain name of a website is exclusive; any mismatch is an indication of a phishing attack. In Chang et al (2013), we had illustrated and proved that it is possible to identify the associated legitimate website from querying the logo image through a Google image search. We applied fixed segmentation with manual best-fit cropping to extract the logo.…”

Section: Introductionmentioning

confidence: 98%

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Utilisation of website logo for phishing detection

Chiew

Chang

Sze

et al. 2015

Computers & Security

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123

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“…In this method, the submission of forms with random inputs and the corresponding responses are captured to decide whether a website is genuine or bogus. This method can detect XSS‐based attacks that many similar tools fail to recognize.Chang et al have employed Google's reverse image search, which is a service from Google to use a picture as a search item and find related images around the web or find the websites that contain that image. In this method, a screenshot of the website is taken and the logo is extracted and uploaded in Google's reverse image search service to get the keywords associated with the the logo.…”

Section: Introductionmentioning

confidence: 99%

Preventing phishing attacks using text and image watermarking

Hajiali

Amirmazlaghani

Kordestani

2018

Concurrency and Computation

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Summary Phishing is a form of identity theft used to illegally gather personal and financial information by providing fake web pages designed to mimic the website of a legitimate business. In this paper, we propose a novel anti‐phishing approach based on using imperceptible watermarking and monitoring the HTTP requests. In the server‐side, a URL dependent watermark is generated and embedded in the elements of the web page, which are logo image and HTML/CSS files. In the client side, to authenticate the website and check its safety, the watermark is regenerated and compared with the extracted watermarks from the elements of the webpage. Security analysis of the proposed method demonstrates its robustness against some common attacks. The proposed method performs fully automatically and without user interaction. It can be simply implemented and used for all kinds of websites, either secured or not secured with SSL protocol.

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Phishing Detection via Identification of Website Identity

Cited by 46 publications

References 6 publications

Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application

Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application

Utilisation of website logo for phishing detection

Preventing phishing attacks using text and image watermarking

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