AI security and cyber risk in IoT systems
Petar Radanliev, David De Roure, Carsten Maple, Jason R.C. Nurse,, Razvan Nicolescu, Uchenna Ani
TL;DR
This paper introduces a dependency model for IoT systems to improve cyber risk estimation and assessment, addressing current challenges in data strategies and cybersecurity.
Contribution
The paper presents a novel dependency model specifically designed for IoT cybersecurity risk assessment and impact analysis.
Findings
Model enables more accurate cyber risk estimation in IoT systems
Provides a framework for assessing risk impact in IoT cybersecurity
Offers recommendations for cybersecurity community to enhance data strategies
Abstract
We present a dependency model tailored to the context of current challenges in data strategies and make recommendations for the cybersecurity community. The model can be used for cyber risk estimation and assessment and generic risk impact assessment.
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Taxonomy
TopicsNetwork Security and Intrusion Detection