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Cybersecurity Challenges in Geoscience Data Management: Securing Critical Geophysical Data from Vulnerabilities and Improving Data Integrity in Exploration

Nyaknno Umoren,Malvern Iheanyichukwu Odum

2023 · DOI: 10.62225/2583049x.2023.3.1.4969
International Journal of Advanced Multidisciplinary Research and Studies · 0 Citations

TLDR

This review examines the principal cybersecurity challenges confronting geoscience data management, including unauthorized access, data tampering, insider threats, and vulnerabilities inherent in legacy systems and cloud-based platforms and proposes a framework for integrating cybersecurity into every phase of geoscience data lifecycles.

Abstract

The exponential growth of geoscience datasets—encompassing seismic surveys, well logs, remote sensing, and reservoir models—has underscored the imperative for robust cybersecurity measures in exploration and production workflows. This review examines the principal cybersecurity challenges confronting geoscience data management, including unauthorized access, data tampering, insider threats, and vulnerabilities inherent in legacy systems and cloud-based platforms. We analyze how emerging threats such as ransomware, advanced persistent threats (APTs), and supply-chain attacks can compromise data integrity, availability, and confidentiality. The paper synthesizes best practices and technological solutions—ranging from encryption and blockchain-enabled audit trails to zero-trust architectures and AI-driven threat detection—that bolster the resilience of geophysical data repositories. Case studies illustrate real-world incidents and response strategies, highlighting lessons learned and areas for improvement. Finally, we propose a framework for integrating cybersecurity into every phase of geoscience data lifecycles, from acquisition and processing to storage and collaborative sharing. By addressing both technical and organizational dimensions, this review aims to guide practitioners in securing critical geophysical assets and ensuring the reliability of data-driven decision-making in exploration.