A Methodical Overview on Phishing Detection along with an Organized Way to Construct an Anti-Phishing Framework
Title | A Methodical Overview on Phishing Detection along with an Organized Way to Construct an Anti-Phishing Framework |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Patil, Srushti, Dhage, Sudhir |
Conference Name | 2019 5th International Conference on Advanced Computing Communication Systems (ICACCS) |
Publisher | IEEE |
ISBN Number | 978-1-5386-9533-3 |
Keywords | account details, Anti Phishing Working Group, Anti-phishing, Anti-Phishing framework, anti-phishing model, Banking, blacklisting, classification, Computer crime, credit card details, emails, feature extraction, Google, HTTPs, Human Behavior, human factor, in-use anti-phishing tools, Internet, machine learning, personal information, phishing, phishing approaches, phishing attack, Phishing Detection, phishing Websites, phishy URL, pubcrawl, Security and Privacy, security attack, Tools, Uniform resource locators, unsolicited e-mail, Web sites, website features |
Abstract | Phishing is a security attack to acquire personal information like passwords, credit card details or other account details of a user by means of websites or emails. Phishing websites look similar to the legitimate ones which make it difficult for a layman to differentiate between them. As per the reports of Anti Phishing Working Group (APWG) published in December 2018, phishing against banking services and payment processor was high. Almost all the phishy URLs use HTTPS and use redirects to avoid getting detected. This paper presents a focused literature survey of methods available to detect phishing websites. A comparative study of the in-use anti-phishing tools was accomplished and their limitations were acknowledged. We analyzed the URL-based features used in the past to improve their definitions as per the current scenario which is our major contribution. Also, a step wise procedure of designing an anti-phishing model is discussed to construct an efficient framework which adds to our contribution. Observations made out of this study are stated along with recommendations on existing systems. |
URL | https://ieeexplore.ieee.org/document/8728356 |
DOI | 10.1109/ICACCS.2019.8728356 |
Citation Key | patil_methodical_2019 |
- pubcrawl
- machine learning
- personal information
- Phishing
- phishing approaches
- phishing attack
- Phishing Detection
- phishing Websites
- phishy URL
- internet
- security and privacy
- security attack
- tools
- Uniform resource locators
- unsolicited e-mail
- Web sites
- website features
- credit card details
- Anti Phishing Working Group
- Anti-phishing
- Anti-Phishing framework
- anti-phishing model
- Banking
- blacklisting
- classification
- Computer crime
- account details
- emails
- feature extraction
- HTTPs
- Human behavior
- human factor
- in-use anti-phishing tools