Systematic Literature Review: Cryptographic Protocols for Securing Genomic Data and Privacy

Abstract

Advances in Next-Generation Sequencing (NGS) technology have enabled large-scale genomic data digitalization to support precision medicine. However, the static, sensitive, and hereditary nature of genomic data poses significant privacy risks for individuals and their families. This study aims to conduct a systematic literature review of modern cryptographic protocols designed to secure genomic data. The research applies a Systematic Literature Review (SLR) approach by analyzing relevant scientific publications from 2018 to 2026 across multiple reputable databases. The findings indicate that Homomorphic Encryption (HE) enables computation on encrypted data without decryption, ensuring strong privacy protection, but faces challenges related to computational efficiency. Secure Multi-party Computation (SMPC) supports secure collaboration across institutions without exposing raw data, although it requires substantial communication and bandwidth resources. Meanwhile, Differential Privacy (DP) provides a more efficient approach but may compromise data accuracy, particularly in clinical decision-making contexts. In addition, hybrid approaches, selective encryption strategies, and the integration of post-quantum cryptography are emerging as promising solutions to address scalability and long-term security challenges in genomic big data. Alignment with regulatory frameworks such as Indonesia’s Personal Data Protection Law is also critical for practical implementation. Therefore, developing adaptive, efficient, and sustainable genomic data security systems is essential to support a secure, ethical, and trustworthy national health data ecosystem.