Analisis Komprehensif Evolusi Rekayasa Sosial: Konvergensi Agentic AI dan Deepfake dalam Ekosistem Digital serta Strategi Mitigasi Berbasis Zero Trust
Keywords:
Agentic AI, Deepfake, Keamanan Siber, Rekayasa Sosial, Zero TrustAbstract
Laporan penelitian ini menyajikan tinjauan sistematis mengenai transformasi fundamental dalam lanskap serangan Social Engineering (Rekayasa Sosial), yang telah berevolusi dari teknik manipulasi psikologis konvensional berbasis teks menjadi operasi siber otonom yang digerakkan oleh Artificial Intelligence (AI). Memasuki periode strategis tahun 2026, ekosistem keamanan digital didominasi oleh konvergensi antara Generative AI, teknologi real-time Deepfake, dan kemunculan Agentic AI yang memiliki kapabilitas untuk melakukan pengintaian dan eksekusi serangan secara mandiri tanpa intervensi manusia. Studi ini secara mendalam menganalisis dua studi kasus representatif: insiden penipuan Deepfake CFO di Hong Kong yang mengakibatkan kerugian finansial masif sebesar US$25,6 juta, serta fenomena serangan Injection pada sistem verifikasi biometrik e-KYC perbankan di Asia Tenggara. Melalui pendekatan kualitatif dengan metode tinjauan literatur sistematis dan analisis studi kasus, penelitian ini mengidentifikasi bahwa metode pertahanan tradisional seperti verifikasi visual dan liveness detection pasif tidak lagi memadai. Penelitian ini mengusulkan adopsi kerangka kerja pertahanan adaptif PREDICT yang mengintegrasikan prinsip Zero Trust Architecture, deteksi liveness aktif multi-modal, dan harmonisasi kepatuhan terhadap regulasi UU PDP di Indonesia serta standar global seperti EU AI Act. Temuan ini memberikan kontribusi teoretis dan praktis bagi pengembangan strategi keamanan siber nasional di tengah eskalasi ancaman berbasis kecerdasan buatan
References
Al-Aswadi, F. N., et al. (2025). Evolving Zero Trust architectures for AI-driven cyber threats in healthcare and other high-risk data environments: A systematic review. International Journal of Environmental Research and Public Health. https://pmc.ncbi.nlm.nih.gov/articles/PMC12229833/
Di Mauro, M., Casola, V., Choo, K. K. R., & Galdi, C. (2025). The erosion of cybersecurity zero-trust principles through generative AI: A survey on the challenges and future directions. Future Internet, 17(1), 5. https://doi.org/10.3390/fi17010005
Jaleel, A., et al. (2025). Cognitive firewalls: Mitigating LLM-powered social engineering through personality-aware behavioral analytics. The American Journal of Engineering and Technology, 7(01), 1-15. https://www.theamericanjournals.com/index.php/tajet/article/view/6943
Kaloudi, N., & Li, J. (2020). The AI-driven threat landscape: A survey of dangers and management strategies. ACM Computing Surveys, 53(1), 1-35. https://doi.org/10.1145/3372819
Nguyen, H. S., et al. (2025). EdgeDoc: Hybrid CNN-transformer model for accurate forgery detection and localization in ID documents. arXiv. https://arxiv.org/abs/2508.16284
NIST. (2024). Adversarial machine learning: A taxonomy and terminology of attacks and mitigations. National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.100-2
Shreshtha, S. (2025). Zero Trust architecture in AI-driven cybersecurity: A machine learning perspective. ResearchGate. https://www.researchgate.net/publication/388523876_Zero_Trust_Architecture_in_AI-Driven_Cybersecurity_A_Machine_Learning_Perspective
Nguyen, H. S., et al. (2025). EdgeDoc: Hybrid CNN-transformer model for accurate forgery detection and localization in ID documents. arXiv. https://arxiv.org/abs/2508.16284
Respati, A. A. (2024). Reformulasi UU ITE terhadap Artificial Intelligence dibandingkan dengan Uni Eropa dan China AI Act regulation. Jurnal USM Law Review, 7(3), 1737-1758. https://doi.org/10.26623/julr.v7i3.10578
Roy, S., et al. (2024). Zero trust and AI: A synergistic approach to next-generation cyber threat mitigation. World Journal of Advanced Research and Reviews, 24(03), 3374-3387. https://doi.org/10.30574/wjarr.2024.24.3.3883
World Economic Forum. (2026). Unmasking cybercrime: Strengthening digital identity verification against deepfakes. https://www.weforum.org/reports/unmasking-cybercrime-strengthening-digital-identity-verification-against-deepfakes-2026
Zhang, X., et al. (2025). Zero Trust Architecture: A systematic literature review. arXiv. https://doi.org/10.48550/arXiv.2503.11659