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Multi-Trace : Multi-level Data Trace Generation with the Cooja Simulator

Finne, Niclas (author)
RISE,Datavetenskap,Research Institutes of Sweden (RISE), Gothenburg, Sweden
Eriksson, Joakim (author)
RISE,Datavetenskap,Research Institutes of Sweden (RISE), Gothenburg, Sweden
Voigt, Thiemo (author)
Uppsala universitet,RISE,Datavetenskap,Uppsala University, Sweden,Datorarkitektur och datorkommunikation,Datorteknik,Research Institutes of Sweden (RISE), Gothenburg, Sweden
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Suciu, George (author)
BEIA, Romania
Sachian, Mari-Anais (author)
BEIA, Romania
Ko, JeongGil (author)
Yonsei University, South Korea
Keipour, Hossein (author)
RISE,Datavetenskap,Research Institutes of Sweden (RISE), Gothenburg, Sweden; Blekinge Institute of Technology (BTH)
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 (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2021
2021
English.
In: 2021 17th International Conference on Distributed Computing in Sensor Systems (DCOSS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665439299 ; , s. 390-395
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Wireless low-power, multi-hop networks are exposed to numerous attacks also due to their resource-constraints. While there has been a lot of work on intrusion detection systems for such networks, most of these studies have considered only a few topologies, scenarios and attacks. One of the reasons for this shortcoming is the lack of sufficient data traces that are required to train many machine learning algorithms. In contrast to other wireless networks, multi-hop networks do not contain one entity that can capture all the traffic which makes it more difficult to acquire such traces. In this paper we present Multi-Trace. Multi-Trace extends the Cooja simulator with multi-level tracing facilities that enable data logging at different levels while maintaining a global time. We discuss the opportunities that traces generated by Multi-Trace enable for researchers interested in input for their machine learning algorithms. We present experiments that show the efficiency with which Multi-Trace generates traces. We expect Multi-Trace to be a useful tool for the research community.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Keyword

Machine learning algorithms
Network topology
Wireless networks
Intrusion detection
Training data
Spread spectrum communication
Machine learning
Security
Data Traces
Internet of Things

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