[심보미] Deepfakes and the AI Arms Race in Bank Cybersecurity

[심보미]

Title: Deepfakes and the AI Arms Race in Bank Cybersecurity

Speaker: Governor Michael S. Barr (미 연준 이사)

Date: April 17, 2025

Word Count: 298 words

https://www.federalreserve.gov/newsevents/speech/barr20250417a.htm

Glossary

1) Generative Adversarial Networks (GANs): 생성적 적대 신경망, 적대적 생성 신경망

2) generator: 생성자

3) discriminator: 판별자

4) Arup: 에이럽(영국의 다국적 엔지니어링 및 컨설팅 기업)

Script

Deepfake attacks are those in which an attacker uses Generative AI (Gen AI) to create a doppelganger with a person's voice or image and uses this doppelganger to interact with individuals or institutions to commit fraud. Deepfake technology is a particularly pernicious vehicle for cybercrime. The process begins with voice synthesis, where Gen AI models can synthesize the speech of their victim not only in words, but also in phrase patterns, tone, and inflection. With just a short sample audio, for example, criminals assisted by Gen AI can impersonate a close relative in a crisis situation or a high-value bank client, seeking to complete a transaction at their bank.

Criminals can also use Gen AI-generated videos to create believable depictions of individuals. For videos, Generative Adversarial Networks (GANs) are the core technology behind most deepfake systems. GANs consist of two competing models, the generator and the discriminator, which compete with and improve each other. This competition results in increasingly realistic, indistinguishable fake images and videos.

Deepfake technology can also be augmented by other AI tools; for instance, criminals can use AI to extract and organize extensive multimodal personal data to facilitate identity verification. Attackers can also turn to "dark web" tools, such as jailbroken versions of popular large language models, where the guardrails have been removed, to learn the deepfake trade and improve their attacks.

I expect that many of you can recall examples of how deepfakes of politicians and prominent business executives have fooled the public and spread disinformation. Deepfakes are also being used to commit payment fraud. In one case in 2024, a sophisticated deepfake of the chief financial officer for British engineering and architectural firm Arup was reportedly deployed in a video meeting and convinced an Arup financial employee to transfer $25 million to thieves.