AI-driven malware protection techniques in mobile environments
Today, mobile devices are an essential part of daily life, making them an attractive target for malware attacks. Traditional malware protection techniques, while effective, face increasing challenges due to constantly evolving threats. This article explores artificial intelligence (AI)-powered malwa...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | Perú |
| Institución: | Universidad de San Martín de Porres |
| Repositorio: | Revistas - Universidad de San Martín de Porres |
| Idioma: | español |
| OAI Identifier: | oai:revistas.usmp.edu.pe:article/2959 |
| Acceso en línea: | https://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/2959 |
| Access Level: | acceso abierto |
| Palabra clave: | Artificial intelligence malware mobile devices security Machine learning malware detection Inteligencia artificial dispositivos móviles seguridad Aprendizaje automático Malware detección de malware |
| Sumario: | Today, mobile devices are an essential part of daily life, making them an attractive target for malware attacks. Traditional malware protection techniques, while effective, face increasing challenges due to constantly evolving threats. This article explores artificial intelligence (AI)-powered malware protection techniques in mobile environments, evaluating their effectiveness compared to traditional methods. Through a systematic analysis of the literature, the advantages of using AI, such as machine and deep learning, to improve malware detection and mitigation on mobile devices are highlighted. Additionally, limitations and challenges of implementing these advanced techniques are identified. |
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