ITEA is the Eureka Cluster on software innovation
ITEA is the Eureka Cluster on software innovation
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Trace Generation support for attack detection

Project
19045 STACK
Type
New system
Description

In order to train machine learning algorithms for attack detection, quite some training data is needed. For low-power wireless mesh networks, such data traces are not available. We have extended the widely used Cooja simulator (that stems from RISE and is used in both academia and industry) has been extended with functionality to create trace files. We have both implemented this tool and made it available as open source.

Contact
Niclas Finne, Joakim Eriksson, Thiemo Voigt, George Suciu, Mari-Anais Sachian, JeongGil Ko, Hossein Keipour
Email
thiemo.voigt@ri.se
Research area(s)
Security, IoT Mesh Networks
Technical features

Able to generate data traces for attack detection

Integration constraints

The tool is an extension of the Cooja simulator that is part of the Contiki-NG software

Targeted customer(s)

Developers (security and machine learning experts) that want to design intrusion detection / anomaly detection etc mechanisms for IoT mesh networks

Conditions for reuse

Part of open software with generous license, can be used by anyone

Confidentiality
Public
Publication date
01-01-2021
Involved partners
RISE - Research institutes of Sweden (SWE)
BEIA Consult International (ROU)
Yonsei University (KOR)