Welcome to our

Cyber Security News Aggregator

.

Cyber Tzar

provide a

cyber security risk management

platform; including automated penetration tests and risk assesments culminating in a "cyber risk score" out of 1,000, just like a credit score.

Using “Master Faces” to Bypass Face-Recognition Authenticating Systems

published on 2021-08-06 11:44:53 UTC by Bruce Schneier
Content:

Fascinating research: “Generating Master Faces for Dictionary Attacks with a Network-Assisted Latent Space Evolution.”

Abstract: A master face is a face image that passes face-based identity-authentication for a large portion of the population. These faces can be used to impersonate, with a high probability of success, any user, without having access to any user-information. We optimize these faces, by using an evolutionary algorithm in the latent embedding space of the StyleGAN face generator. Multiple evolutionary strategies are compared, and we propose a novel approach that employs a neural network in order to direct the search in the direction of promising samples, without adding fitness evaluations. The results we present demonstrate that it is possible to obtain a high coverage of the population (over 40%) with less than 10 master faces, for three leading deep face recognition systems.

Two good articles.

Article: Using “Master Faces” to Bypass Face-Recognition Authenticating Systems - published over 3 years ago.

https://www.schneier.com/blog/archives/2021/08/using-master-faces-to-bypass-face-recognition-authenticating-systems.html   
Published: 2021 08 06 11:44:53
Received: 2021 08 06 12:05:02
Feed: Schneier on Security
Source: Schneier on Security
Category: Cyber Security
Topic: Cyber Security
Views: 6

Custom HTML Block

Click to Open Code Editor