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A Human-Centered Risk Evaluation of Biometric Systems Using Conjoint Analysis

Tetsushi Ohki, Narishige Abe, Hidetsugu Uchida, Shigefumi Yamada

TL;DR

A novel human-centered risk evaluation framework using conjoint analysis to quantify the impact of risk factors, such as surveillance cameras, on attacker’s motivation, allowing comprehensive comparisons across use cases.

Abstract

Biometric recognition systems, known for their convenience, are widely adopted across various fields. However, their security faces risks depending on the authentication algorithm and deployment environment. Current risk assessment methods faces significant challenges in incorporating the crucial factor of attacker's motivation, leading to incomplete evaluations. This paper presents a novel human-centered risk evaluation framework using conjoint analysis to quantify the impact of risk factors, such as surveillance cameras, on attacker's motivation. Our framework calculates risk values incorporating the False Acceptance Rate (FAR) and attack probability, allowing comprehensive comparisons across use cases. A survey of 600 Japanese participants demonstrates our method's effectiveness, showing how security measures influence attacker's motivation. This approach helps decision-makers customize biometric systems to enhance security while maintaining usability.

A Human-Centered Risk Evaluation of Biometric Systems Using Conjoint Analysis

TL;DR

A novel human-centered risk evaluation framework using conjoint analysis to quantify the impact of risk factors, such as surveillance cameras, on attacker’s motivation, allowing comprehensive comparisons across use cases.

Abstract

Biometric recognition systems, known for their convenience, are widely adopted across various fields. However, their security faces risks depending on the authentication algorithm and deployment environment. Current risk assessment methods faces significant challenges in incorporating the crucial factor of attacker's motivation, leading to incomplete evaluations. This paper presents a novel human-centered risk evaluation framework using conjoint analysis to quantify the impact of risk factors, such as surveillance cameras, on attacker's motivation. Our framework calculates risk values incorporating the False Acceptance Rate (FAR) and attack probability, allowing comprehensive comparisons across use cases. A survey of 600 Japanese participants demonstrates our method's effectiveness, showing how security measures influence attacker's motivation. This approach helps decision-makers customize biometric systems to enhance security while maintaining usability.
Paper Structure (16 sections, 6 equations, 3 figures, 6 tables)

This paper contains 16 sections, 6 equations, 3 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Related works
  3. Risk evaluation of Biometrics
  4. ISO/IEC 19795-1:2021
  5. NIST SRE
  6. Study Design
  7. Participants
  8. Designing Conjoint Analysis
  9. Risk Evaluation
  10. Results
  11. Conjoint analysis
  12. Use cases
  13. Discussion and Limitation
  14. Discussion
  15. Limitation
  16. ...and 1 more sections

Figures (3)

  • Figure 1: Overview of our proposal
  • Figure 2: Overview of the study scenario. We planned a scenario in which the in-game challenge is to (1) break into a store with "security measures" and (2) open a safe locked by "biometric recognition" to (3) obtain a "exclusive item.".
  • Figure 3: Example of pairwise comparison task: The actual task was conducted in Japanese, however, we show an English translated version for explanation