A User-friendly Approach to Write and Enforce Rules for Detecting Anomalous Network Traffic in IoT Environments
Author:
Affiliation:
1. Federal University of Pernambuco (UFPE), Recife, Brazil
Funder
RNP
NSF
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3387940.3392248
Reference14 articles.
1. A Realistic Experimental Comparison of the Suricata and Snort Intrusion-Detection Systems
2. Forbes. 2005. 2017 Roundup Of Internet Of Things Forecasts. https://www.forbes.com/sites/louiscolumbus/2017/12/10/2017-roundup-of-internet-of-things-forecasts/#7b71aae11480 Forbes. 2005. 2017 Roundup Of Internet Of Things Forecasts. https://www.forbes.com/sites/louiscolumbus/2017/12/10/2017-roundup-of-internet-of-things-forecasts/#7b71aae11480
3. Intrusion detection system: A comprehensive review
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1. A Usability Study on the creation of Intrusion Detection Rules on IoT Networks;Proceedings of the ACM/IEEE 6th International Workshop on Software Engineering Research & Practices for the Internet of Things;2024-04-20
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