Securing Networks Against Anonymous Invaders

Abstract

The power of anonymity on the internet is being leveraged by criminals, online trolls, and malicious hackers. Cyber criminals masquerade as legitimate users in order to steal valuable private data, commit fraud, and steal money from their victims. This thesis investigates security vulnerabilities that exist as a product of user anonymity and provides a biometric mitigation to one of the most common exploits against DoD personnelsocial engineering. To strip anonymity from malicious users, we used a concept that harkens back to World War II called fist of the sender. This technique was used by allied intelligence analysts to identify enemy units by the rhythm of their radio operators when they transmitted Morse code. We applied the same concept to keystrokes along a keyboard and created a digital fist. Our research used a chatbot that posed as a victim, and we had student-subjects play the role of Social Engineers and attempt to phish the chatbot. Our system measures keystroke dynamics to increase user recognition and introduces specific perturbations during a users typing sessionsometimes by making the caret disappear, and sometimes by suddenly moving the caret back a few spaces. We hypothesized that as a user tried to recover from these interactions, we could increase typing attribution since every users subconscious reaction would be unique. Our results show cases where identification increased over 20% in some cases through the introduction of perturbations.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2019
Accession Number
AD1080387

Entities

People

  • Lucas J. Burke
  • Nathan J. Richardson

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Cyber

DTIC Thesaurus Topics

  • Authentication
  • Biometric Security
  • Computational Science
  • Computer Languages
  • Computer Network Security
  • Computer Programs
  • Computer Science
  • Computers
  • Criminals
  • Engineering
  • Feature Extraction
  • Identification
  • Information Systems
  • Machine Learning
  • Recognition
  • Second World War
  • Social Media

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Cybersecurity.
  • Military History of the United States in the 20th Century.

Technology Areas

  • Cyber
  • Space