Publication Details
Security Monitoring of IoT Communication Using Flows
Ryšavý Ondřej, doc. Ing., Ph.D. (DIFS)
Grégr Matěj, Ing., Ph.D. (DIFS)
Internet of Things, security, monitoring, statistical anomaly detection, IPFIX,
CoAP
Network monitoring is an important part of network management that collects
valuable metadata describing active communication protocols, network
transmissions, bandwidth utilization, and the most communicating nodes.
Traditional IP network monitoring techniques include the SNMP system, flow
monitoring, or system logging. The environment of the Internet of Things (IoT)
networks, however, shows that these approaches do not provide sufficient
visibility of IoT communication which would allow network administrators to
identify possible attacks on IoT nodes. The reason is obvious: IoT devices lack
sufficient computational resources to fully implement monitoring agents, LAN IoT
data communication is often directly over data link layers rather than IP, and
IoT sensors produce an endless flow of small packets which can be difficult to
process in real-time. To tackle these limitations we propose a new IoT monitoring
model based on extended IPFIX records. The model employs a passive monitoring
probe that observes IoT traffic and collects metadata from IoT protocols. Using
extended IPFIX protocol, flow records with IoT metadata are sent to the collector
where they are analyzed and used to provide a global view on the whole IoT
network and its communication. We also present two statistical approaches that
analyze IoT flows data in order to detect security incidents or malfunctioning of
a device. The proof-of-concept implementation is demonstrated for Constrained
Application Protocol (CoAP) traffic in the smart home environment.
@inproceedings{BUT159987,
author="Petr {Matoušek} and Ondřej {Ryšavý} and Matěj {Grégr}",
title="Security Monitoring of IoT Communication Using Flows",
booktitle="Proceedings of the 6th Conference on the Engineering of Computer Based Systems",
year="2019",
series="ECBS '19",
pages="1--9",
publisher="Association for Computing Machinery",
address="New York",
doi="10.1145/3352700.3352718",
isbn="978-1-4503-7636-5",
url="http://doi.acm.org/10.1145/3352700.3352718"
}