Dr Christopher McDermott c.d.mcdermott@rgu.ac.uk
Lecturer
Towards a conversational agent for threat detection in the internet of things.
McDermott, Christopher D.; Jeannelle, Bastien; Isaacs, John P.
Authors
Bastien Jeannelle
Dr John Isaacs j.p.isaacs@rgu.ac.uk
Dean
Abstract
A conversational agent to detect anomalous traffic in consumer IoT networks is presented. The agent accepts two inputs in the form of user speech received by Amazon Alexa enabled devices, and classified IDS logs stored in a DynamoDB Table. Aural analysis is used to query the database of network traffic, and respond accordingly. In doing so, this paper presents a solution to the problem of making consumers situationally aware when their IoT devices are infected, and anomalous traffic has been detected. The proposed conversational agent addresses the issue of how to present network information to non-technical users, for better comprehension, and improves awareness of threats derived from the mirai botnet malware.
Citation
MCDERMOTT, C.D., JEANNELLE, B. and ISAACS, J.P. 2019. Towards a conversational agent for threat detection in the internet of things. In Proceedings of the 2019 International Cyber science on cyber situational awareness, data analytics and assessment (Cyber SA): pioneering research and innovation in cyber situational awareness, 3-4 June 2019, Oxford, UK. Piscataway: IEEE [online], chapter 6. Available from: https://doi.org/10.1109/CyberSA.2019.8899580
Conference Name | 2019 International Cyber science on cyber situational awareness, data analytics and assessment (Cyber SA): pioneering research and innovation in cyber situational awareness |
---|---|
Conference Location | Oxford, UK |
Start Date | Jun 3, 2019 |
End Date | Jun 4, 2019 |
Acceptance Date | Mar 26, 2019 |
Online Publication Date | Nov 14, 2019 |
Publication Date | Nov 14, 2019 |
Deposit Date | Nov 21, 2019 |
Publicly Available Date | Nov 21, 2019 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Chapter Number | Chapter 6 |
DOI | https://doi.org/10.1109/CyberSA.2019.8899580 |
Keywords | Situational awareness; Intrusion detection; Botnet; DDoS; Amazon echo; Alexa; Virtual assistant; Conversational agent |
Public URL | https://rgu-repository.worktribe.com/output/782853 |
Files
MCDERMOTT 2019 Towards a consersational
(276 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc/4.0/
You might also like
Burst detection-based selective classifier resetting.
(2021)
Journal Article
Data stream mining: methods and challenges for handling concept drift.
(2019)
Journal Article
Downloadable Citations
About OpenAIR@RGU
Administrator e-mail: publications@rgu.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search