Extorsión digital con inteligencia artificial en el Perú: revisión sistemática del marco normativo y lineamientos para su prevención
| Pages | 1-7 |
| Date | 05 July 2026 |
| Published date | 05 July 2026 |
| Author | Sarasara Victoria Palomino Firma |
| Subject Matter | Social Sciences |
Extorsión digital con inteligencia artificial en el Perú:
revisión sistemática del marco normativo y
lineamientos para su prevención
Digital extortion using artificial intelligence in Peru: a systematic review of
the regulatory framework and guidelines for its prevention
Recibido: 20/08/2025 - Aceptado: 17/11/2025
Sarasara Victoria Palomino Firma
https://orcid.org/0000-0002-1001-4380
spalominofi@ucvvirtual.edu.pe
Universidad César Vallejo. Lima, Perú
Resumen
Este artículo tiene como finalidad examinar el marco normativo peruano sobre extorsión digital potenciada por IA,
compararlo con estándares internacionales y proponer lineamientos normativo-operativos para su prevención,
persecución y prueba pericial. Empleando metodología de revisión sistemática (PRISMA 2020) de 30 fuentes
académicas, normativas e institucionales (2020–2025), con análisis documental, jurídico-comparado y síntesis
cualitativa temática, obteniéndose como resultados que, la evidencia muestra la capacidad de generación
sintética (deepfakes y clonación de voz) supera la detección humana y algorítmica en contextos reales; el Perú
avanzó con la Ley N.º 32314 (agravante por uso de IA), pero persisten vacíos de procedimientos de retiro ágil de
contenidos, preservación temprana de evidencia y estándares periciales para audio/imagen sintética. En el
derecho comparado, la UE (AI Act), Ofcom (Reino Unido) y eSafety (Australia) establecen obligaciones de
diligencia, transparencia y herramientas de atribución/provenance. En consecuencia, se recomienda la
implementación de un modelo híbrido complemente la sanción penal con deberes de plataformas (detección,
etiquetado y preservación), fortalecimiento de laboratorios forenses y programas de prevención y educación en
ciberseguridad, para mejorar la respuesta estatal y la protección de las víctimas.
Palabras clave: extorsión digital, inteligencia artificial, deepfak es
Abstract
This article aims to ex amine the Peruvian regulatory framework on AI-enhanced digital extortion, compare it with
international standards, and propose normative–operational guidelines for its prevention, prosecution, and forensic
examination. Using a systematic review methodology (PRISMA 2020) of 30 academic, regulatory, and institutional
sources (2020–2025), with documentary, legal-comparative, and th ematic qualitative analysis, the findings show
that synthetic-content generation capabilities (deepfakes and voice cloning) surpass human and algorithmic
detection in real-world contexts . Peru has made progress with La w No. 32314 (aggravating circumstance for the
use of AI); however, gaps remain in procedures for the swift removal of harmful content, early preservation of
evidence, and forensic standards for synthetic audio/image analysis. In comparative law, the EU (AI Act), Ofcom
(United Kingdom), and eSafety (Australia) establish obligations relating to due di ligence, transparency, and
attribution/provenance tools. Consequently, this study c oncludes by recommending a h ybrid model that
complements criminal sanctions wit h platform duties (detection, labeling, and preservation), strengthening of
forensic laboratories, and c ybersecurity prevention and education programs, in order to improve the State’s
response and enhance victim protection.
Keywords: digital extortion, artificial intelligence, deepfakes
Introducción
El delito de extorsión ha experimentado una evolución significativa en las últimas dos décadas, pasando
de modalidades presenciales tradicionales a esquemas digitales altamente sofisticados. Esta transformación se
ha visto impulsada por la masificación de internet, el anonimato en redes sociales y el desarrollo de la inteligencia
artificial (IA), que ha permitido nuevas formas de suplantación de identidad, manipulación audiovisual y chantaje
en entornos virtuales (Europol, 2025; Holt et al., 2022).
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