DocumentCode
2789980
Title
Beyond the lock icon: real-time detection of phishing websites using public key certificates
Author
Zheng Dong ; Kapadia, Apu ; Blythe, Jim ; Camp, L. Jean
Author_Institution
Sch. of Inf. & Comput., Indiana Univ., Bloomington, IN, USA
fYear
2015
fDate
26-29 May 2015
Firstpage
1
Lastpage
12
Abstract
We propose a machine-learning approach to detect phishing websites using features from their X.509 public key certificates. We show that its efficacy extends beyond HTTPS-enabled sites. Our solution enables immediate local identification of phishing sites. As such, this serves as an important complement to the existing server-based anti-phishing mechanisms which predominately use blacklists. Blacklisting suffers from several inherent drawbacks in terms of correctness, timeliness, and completeness. Due to the potentially significant lag prior to site blacklisting, there is a window of opportunity for attackers. Other local client-side phishing detection approaches also exist, but primarily rely on page content or URLs, which are arguably easier to manipulate by attackers. We illustrate that our certificate-based approach greatly increases the difficulty of masquerading undetected for phishers, with single millisecond delays for users. We further show that this approach works not only against HTTPS-enabled phishing attacks, but also detects HTTP phishing attacks with port 443 enabled.
Keywords
Web sites; computer crime; learning (artificial intelligence); public key cryptography; HTTPS-enabled phishing attack; Web site phishing detection; machine-learning approach from; public key certificate; server-based antiphishing mechanism; site blacklisting; Browsers; Electronic mail; Feature extraction; Public key; Servers; Uniform resource locators; certificates; machine learning; security;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Crime Research (eCrime), 2015 APWG Symposium on
Conference_Location
Barcelona
Type
conf
DOI
10.1109/ECRIME.2015.7120795
Filename
7120795
Link To Document