Cyber-Biosecurity Challenges in Next-Generation Sequencing: A Comprehensive Analysis of Emerging Threat Vectors

Next-generation sequencing (NGS) has transformed genomic research and healthcare by enabling the rapid and cost-effective sequencing of DNA and RNA, surpassing traditional techniques such as Sanger sequencing. This technological leap has had a profound impact on fields including biomedical research, personalised medicine, cancer genomics, agriculture, and forensic sciences. With its widespread adoption, NGS has made genomic information more accessible, facilitating the sequencing of millions of genomes. However, the growing reliance on NGS has also brought significant challenges related to cyber-biosecurity, particularly the protection of genomic data against cyber threats such as unauthorised access, data breaches, and exploitation. Genomic data is inherently sensitive, and vulnerabilities in NGS technologies, software, data-sharing practices, and open-access databases expose it to risks concerning data confidentiality, integrity, and privacy. While NGS data plays an indispensable role across numerous sectors, research addressing the cyber-biosecurity of these technologies remains fragmented. Most existing studies focus narrowly on specific areas, such as microbial sequencing or system architecture, and fail to provide a holistic perspective on the security challenges that span the entire NGS workflow. Additionally, the lack of interdisciplinary collaboration between the biotechnology and cybersecurity communities further exacerbates these gaps. This paper seeks to bridge these gaps by thoroughly examining cyber-biosecurity threats throughout the NGS workflow. It introduces a tailored taxonomy specifically designed for NGS, aimed at increasing stakeholder awareness of potential vulnerabilities and threats. Key insights include identifying vulnerabilities at various stages of the NGS process—from data generation to analysis and storage—and categorising these threats systematically. The study highlights critical gaps in current research, underscoring the need for interdisciplinary collaboration between experts in biotechnology and cybersecurity. It calls for focused efforts to mitigate risks associated with unauthorised access, data misuse, and exploitation. Failure to address these vulnerabilities could result in severe consequences, such as breaches of medical confidentiality, ethical concerns, and the potential for misuse in malicious applications like genetic warfare or bioterrorism. By providing a comprehensive analysis, this paper advocates for intensified research efforts and collaborative strategies to protect genomic data and ensure its ethical and secure use.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3552069
Citations
7
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
5.64
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article

Cyber-Biosecurity Challenges in Next-Generation Sequencing: A Comprehensive Analysis of Emerging Threat Vectors

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IEEE Access
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article

Cyber-Biosecurity Challenges in Next-Generation Sequencing: A Comprehensive Analysis of Emerging Threat Vectors

Nasreen Anjum, Abu Alam, Hani Alshahrani, M S Kiran, Asadullah Shaikh, Mahreen-ul-Hassan, Shah Raz
article en
7 citations

Abstract

Next-generation sequencing (NGS) has transformed genomic research and healthcare by enabling the rapid and cost-effective sequencing of DNA and RNA, surpassing traditional techniques such as Sanger sequencing. This technological leap has had a profound impact on fields including biomedical research, personalised medicine, cancer genomics, agriculture, and forensic sciences. With its widespread adoption, NGS has made genomic information more accessible, facilitating the sequencing of millions of genomes. However, the growing reliance on NGS has also brought significant challenges related to cyber-biosecurity, particularly the protection of genomic data against cyber threats such as unauthorised access, data breaches, and exploitation. Genomic data is inherently sensitive, and vulnerabilities in NGS technologies, software, data-sharing practices, and open-access databases expose it to risks concerning data confidentiality, integrity, and privacy. While NGS data plays an indispensable role across numerous sectors, research addressing the cyber-biosecurity of these technologies remains fragmented. Most existing studies focus narrowly on specific areas, such as microbial sequencing or system architecture, and fail to provide a holistic perspective on the security challenges that span the entire NGS workflow. Additionally, the lack of interdisciplinary collaboration between the biotechnology and cybersecurity communities further exacerbates these gaps. This paper seeks to bridge these gaps by thoroughly examining cyber-biosecurity threats throughout the NGS workflow. It introduces a tailored taxonomy specifically designed for NGS, aimed at increasing stakeholder awareness of potential vulnerabilities and threats. Key insights include identifying vulnerabilities at various stages of the NGS process—from data generation to analysis and storage—and categorising these threats systematically. The study highlights critical gaps in current research, underscoring the need for interdisciplinary collaboration between experts in biotechnology and cybersecurity. It calls for focused efforts to mitigate risks associated with unauthorised access, data misuse, and exploitation. Failure to address these vulnerabilities could result in severe consequences, such as breaches of medical confidentiality, ethical concerns, and the potential for misuse in malicious applications like genetic warfare or bioterrorism. By providing a comprehensive analysis, this paper advocates for intensified research efforts and collaborative strategies to protect genomic data and ensure its ethical and secure use.

IEEE AccessVol. 13
Shaheed Benazir Bhutto Women University Peshawar (PK), University of Gloucestershire (GB), Najran University (SA), Anglia Ruskin University (GB), University of Portsmouth (GB)
Openalex Percentile: Top 4%
CRISPR and Genetic Engineering
5.64
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