Classification of Threat Level in Typing Activity Through Keystroke Dynamics

Amith K. Belman, Swathi Sridhara, Vir V. Phoha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

System intrusion is a major issue in today's data-driven world. Discovering adversarial activities before or as they happen, through any modality, makes a system more secure. A straight forward approach to determine threat level from typing data would be to analyze the text directly. However, natural language processing is hard to implement on complex real life data, therefore we explore how far keystroke dynamics can go in terms of classifying threat levels correctly. We show that keystroke dynamics (KD) on a desktop can be used to classify the type of activity, either benign or adversarial, that a text sample originates from. We show the inefficiencies of popular temporal features for this task. With our proposed set of 14 features we achieve high accuracies (93% to 97%) and low Type 1 and Type 2 errors (3% to 8%) in classifying text samples of different sizes. We further reduce our feature set to eight using correlation analysis with marginal trade-offs in accuracy and error rates. We collected data from 102 users for benign activities and 103 users for adversarial activities recording over 1.9 million keystroke events in total. Our experiments show that a user's typing behavior can reveal the nature of the typing activity, thereby providing vital cues of a system's threat level.

Original languageEnglish (US)
Title of host publication2020 International Conference on Artificial Intelligence and Signal Processing, AISP 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728144580
DOIs
StatePublished - Jan 2020
Event2020 International Conference on Artificial Intelligence and Signal Processing, AISP 2020 - Amaravati, India
Duration: Jan 10 2020Jan 12 2020

Publication series

Name2020 International Conference on Artificial Intelligence and Signal Processing, AISP 2020

Conference

Conference2020 International Conference on Artificial Intelligence and Signal Processing, AISP 2020
CountryIndia
CityAmaravati
Period1/10/201/12/20

Keywords

  • Context
  • Keystroke-Features
  • Keystrokes
  • Threat-Level
  • Typing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Decision Sciences (miscellaneous)
  • Health Informatics

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  • Cite this

    Belman, A. K., Sridhara, S., & Phoha, V. V. (2020). Classification of Threat Level in Typing Activity Through Keystroke Dynamics. In 2020 International Conference on Artificial Intelligence and Signal Processing, AISP 2020 [9073079] (2020 International Conference on Artificial Intelligence and Signal Processing, AISP 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AISP48273.2020.9073079