Detecting Dynamic Security Threats in Multi-Component IoT Systems

Date
2019-01-08
Authors
Shrestha, Isaac
Hale, Matthew
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
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.
Description
Keywords
Cyber Threat Intelligence and Analytics, Software Technology, Internet of Things,Security,Threat Analysis,Vulnerabilities,Wearables,
Citation
Extent
10 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 52nd Hawaii International Conference on System Sciences
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.