User Authentication from Web Browsing Behavior

Abstract

As anticipated in True Names by Vernor Vinge, identity has been recognized as our most valued possession in cyberspace. Attribution is a key concept in enabling trusted identities and deterring malicious activities. As more people use the Web to communicate, work, and otherwise have fun, is it possible to uniquely identify someone based on their Web browsing behavior or to differentiate between two persons based solely on their Web browsing histories? Based on a user study, this paper provides some insights into these questions. We describe characteristic features of Web browsing behavior and present our algorithm and analysis of an ensemble learning approach leveraging from those features for user authentication.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2013
Accession Number
ADA599778

Entities

People

  • David W. Aha
  • Myriam Abramson

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Anomaly Detection
  • Artificial Intelligence
  • Authentication
  • Change Detection
  • Computer Access Control
  • Computing Devices
  • Cyberspace
  • Data Mining
  • Detection
  • Identification
  • Information Processing
  • Information Science
  • Kernel Functions
  • Machine Learning
  • Social Media
  • Supervised Machine Learning
  • Websites

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Systems Analysis and Design

Technology Areas

  • Cyber
  • Cyber - Cryptography