AI Bibliography
AI Bibliography |
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Nurse, J. R., Creese, S., & De Roure, D. (2017). Security risk assessment in internet of things systems. IT professional, 19(5), 20–26. |
| Resource type: Journal Article BibTeX citation key: Nurse2017 View all bibliographic details  |
Categories: Artificial Intelligence, Complexity Science, Computer Science, Decision Theory, General, Mathematics Subcategories: Analytics, Autonomous systems, Cloud computing, Edge AI, Internet of things, Neural nets Creators: Creese, De Roure, Nurse Publisher: Collection: IT professional |
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Information security risk assessment methods have served us well over the past two decades. They have provided a tool for organizations and governments to use in protecting themselves against pertinent risks. As the complexity, pervasiveness, and automation of technology systems increases and cyberspace matures, particularly with the Internet of Things (IoT), there is a strong argument that we will need new approaches to assess risk and build trust. The challenge with simply extending existing assessment methodologies to IoT systems is that we could be blind to new risks arising in such ecosystems. These risks could be related to the high degrees of connectivity present or the coupling of digital, cyber-physical, and social systems. This article makes the case for new methodologies to assess risk in this context that consider the dynamics and uniqueness of the IoT while maintaining the rigor of best practice in risk assessment.
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