Enhancing Cyber Defense Mechanisms for Genomic Data in Personalized Healthcare Systems
DOI:
https://doi.org/10.5281/zenodo.13852606Keywords:
genomic data security, cybersecurity frameworks, personalized healthcare, intrusion detection systems, encryption techniques, data privacy complianceAbstract
In the era of personalized medicine, genomic data emerges as a cornerstone for tailored healthcare solutions, offering unprecedented opportunities for disease prediction and prevention. However, this sensitive data is increasingly vulnerable to cyber threats that compromise patient privacy and system integrity. Addressing this critical issue, our research introduces a novel cybersecurity framework specifically designed to protect genomic information within healthcare systems. We develop and implement advanced cryptographic methods, real-time intrusion detection systems, and secure data sharing protocols to construct a robust defense mechanism. Through extensive simulations, we evaluate the efficacy of our framework against a range of cyber threats, demonstrating significant enhancements in security measures. Our findings reveal that the proposed solution not only fortifies the security of genomic data but also ensures compliance with regulatory standards and ethical guidelines. This paper contributes a methodologically sound approach to cybersecurity in healthcare, proposing a scalable and efficient framework that paves the way for safer genomic data handling in the realm of personalized medicine.
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Copyright (c) 2024 Ammar Alzaydi, Kahtan Abedalrhman, Siti Nurhaliza, Mohd Ismail
This work is licensed under a Creative Commons Attribution 4.0 International License.
