Proceedings ArticleDOI
An integrated approach to detect phishing mail attacks: a case study
R. Suriya,K. Saravanan,Arunkumar Thangavelu +2 more
- pp 193-199
TLDR
An approach to create a resilient and effective method that uses fuzzy logic to quantify and qualify all the website phishing characteristics and factors in order to detect phishing websites to assess whether phishing activity is taking place or not is proposed.Abstract:
Phishing is a process of luring unsuspecting Internet users to a fake website by using authentic looking email and messages for fraudulent purposes. Most preferred way that the phishers employ to lure victims is through a mass email, constructed to look like an authentic message from a well-known company. Phishing website has its own technical and social problem with each other and being a very complicate and complex issue to understand and analyze, to till date there exist no known single silver bullet to solve it entirely. Here an approach to create a resilient and effective method is proposed that uses fuzzy logic to quantify and qualify all the website phishing characteristics and factors in order to detect phishing websites to assess whether phishing activity is taking place or not. The approach visualizes the webpage in three layers of which the first layer, Domain Name checker, is fully based on characteristics of hyperlinks, the second, Code Script Checker which checks out for the tricks of the attackers in a way how they use JavaScript to hide information from user, and potentially launch sophisticated attacks, and the last layer of our approach, Page Content Checker, checks for phishing site based on its sub criteria. Finally if any of them (with regards to the true one) is higher than its corresponding preset threshold then that webpage is reported as a phishing suspect.read more
Citations
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Proceedings ArticleDOI
High-performance content-based phishing attack detection
TL;DR: A cadre of file matching algorithms is implemented to detect phishing websites based on their content, employing a custom data set consisting of 17,992 phishing attacks targeting 159 different brands and demonstrating that some can achieve a detection rate of greater than 90% while maintaining a low false positive rate.
Proceedings Article
Clustering potential phishing websites using DeepMD5
TL;DR: An attempt to create an automated method that produces clusters of phishing websites with the same brand and evidence suggests created by the same phishing group or individual is described in this paper.
Proceedings ArticleDOI
Phishing website detection fuzzy system modelling
Phoebe Barraclough,Graham Sexton +1 more
TL;DR: This study investigates and identifies parameters in a single platform based on fuzzy system and neural network for phishing websites detection and achieves the best performance compared to other results in the field.
Journal ArticleDOI
Email Phishing: An Enhanced Classification Model to Detect Malicious URLs
TL;DR: An Enhanced Malicious URLs Detection (EMUD) model is developed with machine learning techniques for better classification and accurate results.
Proceedings ArticleDOI
Intelligent phishing detection parameter framework for E-banking transactions based on Neuro-fuzzy
TL;DR: This study presents a novel parameter tuning framework based on a neuron-fuzzy system with comprehensive features, which can enhance system performance in realtime and will provide guidance to the researchers who are using similar techniques in the field.
References
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Proceedings ArticleDOI
Cantina: a content-based approach to detecting phishing web sites
TL;DR: The design, implementation, and evaluation of CANTINA, a novel, content-based approach to detecting phishing web sites, based on the TF-IDF information retrieval algorithm, are presented.
Proceedings Article
Client-Side Defense Against Web-Based Identity Theft.
TL;DR: A framework for client-side defense is proposed: a browser plug-in that examines web pages and warns the user when requests for data may be part of a spoof attack.
Book ChapterDOI
On the Effectiveness of Techniques to Detect Phishing Sites
TL;DR: Over a period of three weeks, the effectiveness of the blacklists maintained by Google and Microsoft with 10,000 phishing URLs was tested, and the existence of page properties that can be used to identify phishing pages were explored.
Proceedings ArticleDOI
Online Detection and Prevention of Phishing Attacks
Juan Chen,Chuanxiong Guo +1 more
TL;DR: This paper proposes a new end-host based anti-phishing algorithm, which it is called LinkGuard, by utilizing the generic characteristics of the hyperlinks in phishing attacks, derived by analyzing the phishing data archive provided by the anti- phishing working group (APWG).
Proceedings ArticleDOI
Intelligent Phishing Website Detection System using Fuzzy Techniques
TL;DR: A novel approach to overcome the 'fuzziness' in traditional Website phishing risk assessment is presented and an intelligent resilient and effective model for detecting phishing Websites is proposed.