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Detecting Dynamic Security Threats in Multi-Component IoT Systems

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Item Summary

Title:Detecting Dynamic Security Threats in Multi-Component IoT Systems
Authors:Shrestha, Isaac
Hale, Matthew
Keywords:Cyber Threat Intelligence and Analytics
Software Technology
Internet of Things,Security,Threat Analysis,Vulnerabilities,Wearables,
Date Issued:08 Jan 2019
Abstract:The rising ubiquity of the Internet of Things (IoT) has heralded a new era of increasingly prolific and damaging IoT-centric security threat vectors. Fast-paced market demand for multi-featured IoT products urge companies, and their software engineers, to bring products to market quickly, often at the cost of security. Lack of proper security threat analysis tooling during development, testing, and release cycles exacerbate security concerns. In this paper, we augment a security threat analysis tool to use audit hooks, open-source information capture components, and machine learning techniques to profile dynamic wearable and IoT operations spanning multiple components during execution. Our tool encourages data-drive threat identification and analysis approaches that can help software engineers perform dynamic testing and threat analysis to mitigate code-level vulnerabilities that lead to attacks in IoT applications. Our approach is evaluated by means of a case study involving a system evaluation across several common attack vectors.
Pages/Duration:10 pages
URI/DOI:http://hdl.handle.net/10125/60151
ISBN:978-0-9981331-2-6
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Cyber Threat Intelligence and Analytics


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