Digital security and privacy

At NR, we have more than 20 years of experience in applied research and industrial development of digital security. We have developed several methods and tools that help system owners identify, design, operate and evaluate cost-effective technologies for this area, and offer services such as training, consulting, development and analysis.

Our specific competence fields cover:

• Adaptive security

We research adaptive security to enable organizations to continuously assess risk and automatically plan for mitigation measures in the past and in the right context, thus improving their ability to respond to current and future security risks.

Adaptive Security continuously collects and analyzes security-related data and incidents to protect against and adapt to known and unknown security incidents before they occur. It learns and adapts to changing environments while driving in the face of changing threats, anticipates threats before they occur, and
dynamically reconfigures the protection mechanisms.

NR has expertise in the development of adaptive techniques and algorithms that will predict and measure the risk of injury and adapt their decisions to these predictions.

Data security

Data security is a large and comprehensive field addressing protection of sensitive data, where confidentiality, integrity, and authenticity are the most common security goals. Data security affects several elements of society and requires knowledge and expertise from different disciplines such as security management, cryptography, information and communication technology, and mathematics. Our research covers various aspects of data security, and we conduct security and privacy assessment, as well as risk and vulnerability assessment, on different levels, including methods, information systems, and organizations. Requirements specification, impact assessment, design and verification.

Privacy 

Rules and regulation for handling personal data are addressed by the Norwegian Personal Data Act and the EU’s Personal Data Protection Regulation (GDPR), which ensures privacy in several areas, such as the right to access, delete and restrict personal data. These regulations emphasise protection of sensitive personal data. Preserving privacy of personal data is relevant in many areas, such as healthcare, finance, banking, insurance, police, etc. Personally identifiable information can point to specific individuals. To meet the privacy requirements when analysing such data, anonymization techniques can be employed for identification and protection of personally identifiable information. However, this may not be a trivial task. As such, we have expertise in methods for privacy-preservation and data anonymization. 

Machine learning and artificial intelligence are central to data analytics. Using confidential computing methods, such as homomorphic encryption, we can analyse the encrypted data and produce meaningful inferences while preserving data privacy