Logo del repository
  1. Home
 
Opzioni

Detection of Hidden Fraudulent URLs within Trusted Sites using Lexical Features

SORIO, ENRICO
•
BARTOLI, Alberto
•
MEDVET, Eric
2013
  • conference object

Abstract
Internet security threats often involve the fraudulent modification of a web site, often with the addition of new pages at URLs where no page should exist. Detecting the existence of such hidden URLs is very difficult because they do not appear during normal navigation and usually are not indexed by search engines. Most importantly, drive-by attacks leading users to hidden URLs, for example for phishing credentials, may fool even tech-savvy users, because such hidden URLs are increasingly hosted within trusted sites, thereby rendering HTTPS authentication ineffective. In this work, we propose an approach for detecting such URLs based only on their lexical features, which allows alerting the user before actually fetching the page. We assess our proposal on a dataset composed of thousands of URLs, with promising results.
DOI
10.1109/ARES.2013.31
Archivio
http://hdl.handle.net/11368/2689964
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84892390294
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6657247
Diritti
metadata only access
Soggetti
  • phishing

  • Web site defacement

Scopus© citazioni
8
Data di acquisizione
Jun 7, 2022
Vedi dettagli
google-scholar
Get Involved!
  • Source Code
  • Documentation
  • Slack Channel
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your nstitution's web identity.

Need professional help?

The original creators of DSpace-CRIS at 4Science can take your project to the next level, get in touch!

Realizzato con Software DSpace-CRIS - Estensione mantenuta e ottimizzata da 4Science

  • Impostazioni dei cookie
  • Informativa sulla privacy
  • Accordo con l'utente finale
  • Invia il tuo Feedback