Visible to the public Network Scanning and Mapping for IIoT Edge Node Device Security

TitleNetwork Scanning and Mapping for IIoT Edge Node Device Security
Publication TypeConference Paper
Year of Publication2019
AuthorsNiedermaier, Matthias, Fischer, Florian, Merli, Dominik, Sigl, Georg
Conference Name2019 International Conference on Applied Electronics (AE)
Date PublishedSept. 2019
PublisherIEEE
ISBN Number978-8-0261-0812-2
Keywordsbuilding block, composability, computer network security, edge detection, edge device, Hardware, iiot, IIoT edge node device security, IIoT edge node sensors, Image edge detection, industrial control, industrial environment, Industrial Internet of Things, industrial networks, Internet of Things, light emitting diodes, MCU, Metrics, microcontroller units, microcontrollers, Monitoring, network scanning, network services, performance evaluation, predictive maintenance, pseudorandom periodic manner, pubcrawl, Resiliency, Scalability, scanning procedure, security, security of data, Servers
Abstract

The amount of connected devices in the industrial environment is growing continuously, due to the ongoing demands of new features like predictive maintenance. New business models require more data, collected by IIoT edge node sensors based on inexpensive and low performance Microcontroller Units (MCUs). A negative side effect of this rise of interconnections is the increased attack surface, enabled by a larger network with more network services. Attaching badly documented and cheap devices to industrial networks often without permission of the administrator even further increases the security risk. A decent method to monitor the network and detect "unwanted" devices is network scanning. Typically, this scanning procedure is executed by a computer or server in each sub-network. In this paper, we introduce network scanning and mapping as a building block to scan directly from the Industrial Internet of Things (IIoT) edge node devices. This module scans the network in a pseudo-random periodic manner to discover devices and detect changes in the network structure. Furthermore, we validate our approach in an industrial testbed to show the feasibility of this approach.

URLhttps://ieeexplore.ieee.org/document/8867032
DOI10.23919/AE.2019.8867032
Citation Keyniedermaier_network_2019