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

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Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application. / Marchal, S.; Armano, G.; Gröndahl, T.; Saari, K.; Singh, Nidhi; Asokan, N.

In: IEEE Transactions on Computers, Vol. 66, No. 10, 01.10.2017, p. 1717-1733.

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@article{c8300e1dce244983be73e6172abc26c4,
title = "Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application",
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.",
keywords = "Browsers, Detectors, Electronic mail, Feature extraction, Privacy, Real-time systems, Uniform resource locators, Phishing webpage detection, browser add-on, machine learning, phishing prevention, phishing target identification, web security",
author = "S. Marchal and G. Armano and T. Gr{\"o}ndahl and K. Saari and Nidhi Singh and N. Asokan",
year = "2017",
month = "10",
day = "1",
doi = "10.1109/TC.2017.2703808",
language = "English",
volume = "66",
pages = "1717--1733",
journal = "IEEE Transactions on Computers",
issn = "0018-9340",
publisher = "IEEE Computer Society",
number = "10",

}

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TY - JOUR

T1 - Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application

AU - Marchal, S.

AU - Armano, G.

AU - Gröndahl, T.

AU - Saari, K.

AU - Singh, Nidhi

AU - Asokan, N.

PY - 2017/10/1

Y1 - 2017/10/1

N2 - 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.

AB - 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.

KW - Browsers

KW - Detectors

KW - Electronic mail

KW - Feature extraction

KW - Privacy

KW - Real-time systems

KW - Uniform resource locators

KW - Phishing webpage detection

KW - browser add-on

KW - machine learning

KW - phishing prevention

KW - phishing target identification

KW - web security

U2 - 10.1109/TC.2017.2703808

DO - 10.1109/TC.2017.2703808

M3 - Article

VL - 66

SP - 1717

EP - 1733

JO - IEEE Transactions on Computers

JF - IEEE Transactions on Computers

SN - 0018-9340

IS - 10

ER -

ID: 15241465