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Protección corporativa contra deepfakes

Authors: Illera Diaz, Mauricio Alan;

Protección corporativa contra deepfakes

Abstract

La irrupción de los deepfakes en tiempo real representa uno de los mayores desafíos contemporáneos para el gobierno corporativo, la toma de decisiones ejecutivas y la continuidad del negocio. A diferencia de las amenazas digitales tradicionales, esta tecnología no busca vulnerar sistemas, sino manipular la percepción humana de identidad, autoridad y legitimidad durante interacciones en vivo, explotando la confianza organizacional como principal vector de ataque. Este documento establece un marco integral para la prevención, detección y respuesta ante deepfakes, con especial énfasis en su impacto estratégico, psicológico, legal y operativo dentro de las organizaciones. Parte de un principio rector ineludible: la imagen y la voz han dejado de ser mecanismos válidos de autenticación de identidad. El manual está dirigido a CEOs, Consejos de Administración y Alta Dirección, proporcionando lineamientos claros de gobierno corporativo, asignación de responsabilidades, controles preventivos, protocolos de respuesta inmediata y criterios de diligencia debida, con enfoque específico en el contexto legal mexicano. Más allá de la dimensión tecnológica, el texto aborda el factor humano como eje central del riesgo, analizando los sesgos cognitivos, la manipulación emocional y el impacto cultural que los deepfakes generan en la confianza interna, la reputación institucional y la responsabilidad fiduciaria de los líderes. Esta publicación no se presenta como una guía teórica, sino como un instrumento normativo y estratégico, diseñado para integrarse a los sistemas de gestión de riesgos, cumplimiento, seguridad corporativa y continuidad del negocio, permitiendo a las organizaciones demostrar preparación, madurez y responsabilidad frente a una amenaza activa y creciente.

Keywords

Deepfake, Real-time deepfake, Risk Management, Artificial intelligence, Governance, Artificial intelligence risk, Crop Protection/statistics & numerical data, Legal compliance, Crop Protection/statistics & numerical data, cibersecurity, Digital fraud, Data protection

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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