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Privacy regulations are laws and rules that govern how organizations collect, use, store, and share personal data of individuals. IT/OT data handling refers to the management of information technology (IT) and operational technology (OT) data, which are often used to monitor and control industrial processes and systems.
Some of the biggest challenges to privacy regulations impacting IT/OT data handling are:
- Compliance: IT/OT data may be subject to different privacy regulations depending on the jurisdiction, sector, and purpose of the data processing. For example, IT/OT data may fall under the scope of the General Data Protection Regulation (GDPR) in the European Union, the California Consumer Privacy Act (CCPA) in the United States, or the Personal Information Protection and Electronic Documents Act (PIPEDA) in Canada. Compliance with these regulations may require implementing technical and organizational measures, such as data minimization, encryption, anonymization, consent management, and breach notification12.
- Security: IT/OT data may be vulnerable to cyberattacks, data breaches, and unauthorized access, which can compromise the privacy and safety of the data subjects and the integrity and availability of the data systems. Security risks may arise from the convergence of IT and OT networks, the use of legacy or outdated devices, the lack of security awareness and training, and the complexity and diversity of the IT/OT environment34.
- Ethics: IT/OT data may raise ethical issues, such as data ownership, data quality, data governance, data accountability, and data transparency. These issues may affect the trust and confidence of the data subjects, the data providers, and the data users, as well as the social and environmental impact of the data processing. Ethics may also influence the design and implementation of the IT/OT systems, such as the use of artificial intelligence, machine learning, and big data analytics .
Some of the current solutions to privacy regulations impacting IT/OT data handling are:
- Frameworks: The NIST Privacy Framework is a voluntary tool that helps organizations identify and manage privacy risks, align privacy practices with business objectives, and demonstrate compliance with privacy regulations. Similarly, the IEC 62443 series of standards provides a framework for securing industrial automation and control systems.
- Technologies: Differential privacy is a technique that adds noise to the data or the query results to prevent the identification or re-identification of individual data subjects. Likewise, homomorphic encryption is a technique that allows performing computations on encrypted data without decrypting it, thus preserving the confidentiality and integrity of the data.
- Strategies: Privacy-by-design is a strategy that embeds privacy into the entire lifecycle of the IT/OT systems, from the initial conception to the final disposal. Similarly, a privacy impact assessment is a strategy that evaluates the potential privacy risks and impacts of the IT/OT systems and proposes mitigation measures.
The future of privacy regulations impacting IT/OT data handling is uncertain, but dynamic. Privacy regulations are likely to evolve and expand in response to the rapid development and adoption of IT/OT technologies, the growing demand and expectation of data subjects, and the increasing complexity and diversity of the IT/OT landscape. Privacy regulations may also vary and conflict across different jurisdictions, sectors, and purposes, creating challenges and opportunities for cross-border and cross-sector data sharing and collaboration. Privacy regulations may also influence and be influenced by the innovation and advancement of IT/OT technologies, such as the Internet of Things, cloud computing, and blockchain .
Learn more about privacy regulations impacting IT/OT data handling and future trends: