Security Implications of Deepfakes in Face Authentication

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU150904" target="_blank" >RIV/00216305:26230/24:PU150904 - isvavai.cz</a>

Result on the web

<a href="https://dl.acm.org/doi/10.1145/3605098.3635953" target="_blank" >https://dl.acm.org/doi/10.1145/3605098.3635953</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3605098.3635953" target="_blank" >10.1145/3605098.3635953</a>

Result language

angličtina

Original language name

Security Implications of Deepfakes in Face Authentication

Original language description

Deepfakes are media generated by deep learning and are nearly indistinguishable from real content to humans. Deepfakes have seen a significant surge in popularity in recent years. There have been numerous papers discussing their effectiveness in deceiving people. What's equally, if not more concerning, is the potential vulnerability of facial and voice recognition systems to deepfakes. The misuse of deepfakes to spoof automated facial recognition systems can threaten various aspects of our lives, including financial security and access to secure locations. This issue remains largely unexplored. Thus, this paper investigates the technical feasibility of a spoofing attack on facial recognition. Firstly, we perform a threat analysis to understand what facial recognition use cases allow the execution of deepfake spoofing attacks. Based on this analysis, we define the attacker model for these attacks on facial recognition systems. Then, we demonstrate the ability of deepfakes to spoof two commercial facial recognition systems. Finally, we discuss possible means to prevent such spoofing attacks.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the ACM Symposium on Applied Computing

ISBN

979-8-4007-0243-3

ISSN

—

e-ISSN

—

Number of pages

9

Pages from-to

1376-1384

Publisher name

Association for Computing Machinery

Place of publication

Avila

Event location

Avila

Event date

Apr 8, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001236958200199