A Review of Public Datasets for Keystroke-based Behavior Analysis

• 영문명: A Review of Public Datasets for Keystroke-based Behavior Analysis
• 발행기관: 한국스마트미디어학회
• 저자명: Kolmogortseva Karina Soo-Hyung Kim Aera Kim
• 간행물 정보: 『스마트미디어저널』Vol13, No.7, 18~26쪽, 전체 9쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2024.07.31

국문 초록

One of the newest trends in AI is emotion recognition utilizing keystroke dynamics, which leverages biometric data to identify users and assess emotional states. This work offers a comparison of four datasets that are frequently used to research keystroke dynamics: BB-MAS, Buffalo, Clarkson II, and CMU. The datasets contain different types of data, both behavioral and physiological biometric data that was gathered in a range of environments, from controlled labs to real work environments. Considering the benefits and drawbacks of each dataset, paying particular attention to how well it can be used for tasks like emotion recognition and behavioral analysis. Our findings demonstrate how user attributes, task circumstances, and ambient elements affect typing behavior. This comparative analysis aims to guide future research and development of applications for emotion detection and biometrics, emphasizing the importance of collecting diverse data and the possibility of integrating keystroke dynamics with other biometric measurements.

목차

Ⅰ. INTRODUCTION

Ⅱ. RELATED WORK

Ⅲ. Comparative Analysis of Datasets

Ⅳ. Discussion

Ⅴ. Conclusion and Future Work

REFERENCES

키워드

computing emotion detection data collection biometric authentication mood analysis