Projects per year
Abstract
Active automata learning became a popular tool for the behavioral analysis of communication protocols. The main advantage is that no manual modeling effort is required since a behavioral model is automatically inferred from a black-box system. However, several real-world applications of this technique show that the overhead for the establishment of an active interface might hamper the practical applicability. Our recent work on the active learning of Bluetooth Low Energy (BLE) protocol found that the active interaction creates a bottleneck during learning. Considering the automata learning toolset, passive learning techniques appear as a promising solution since they do not require an active interface to the system under learning. Instead, models are learned based on a given data set. In this paper, we evaluate passive learning for two network protocols: BLE and Message Queuing Telemetry Transport (MQTT). Our results show that passive techniques can correctly learn with less data than required by active learning. However, a general random data generation for passive learning is more expensive compared to the costs of active learning.
Original language | English |
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Title of host publication | Formal Methods for Autonomous Systems and Automated and verifiable Software sYstem DEvelopment |
Pages | 1-19 |
Number of pages | 19 |
Volume | 371 |
DOIs | |
Publication status | Published - 27 Sept 2022 |
Event | 4th International Workshop on Formal Methods for Autonomous Systems, FMAS 2022 and 4th International Workshop on Automated and Verifiable Software sYstem DEvelopment: FMAS / ASYDE 2022 - Berlin, Germany Duration: 26 Sept 2022 → 27 Sept 2022 |
Publication series
Name | Electronic Proceedings in Theoretical Computer Science, EPTCS |
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Publisher | National ICT Australia Ltd |
ISSN (Print) | 2075-2180 |
Workshop
Workshop | 4th International Workshop on Formal Methods for Autonomous Systems, FMAS 2022 and 4th International Workshop on Automated and Verifiable Software sYstem DEvelopment |
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Country/Territory | Germany |
City | Berlin |
Period | 26/09/22 → 27/09/22 |
Keywords
- Model learning
- Bluetooth Low Energy
- Active automata learning
- Passive automata learning
- MQTT
- Network protocols
ASJC Scopus subject areas
- Software
Projects
- 2 Finished
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LearnTwins - Learning Digital Twins for the Validation and Verification of Dependable Cyber-PhysicalSystems
Aichernig, B. (Co-Investigator (CoI))
1/12/20 → 30/11/23
Project: Research project
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Dependable Internet of Things
Boano, C. A. (Co-Investigator (CoI)), Kubin, G. (Co-Investigator (CoI)), Bloem, R. (Co-Investigator (CoI)), Horn, M. (Co-Investigator (CoI)), Pernkopf, F. (Co-Investigator (CoI)), Zakany, N. (Co-Investigator (CoI)), Mangard, S. (Co-Investigator (CoI)), Witrisal, K. (Co-Investigator (CoI)), Römer, K. U. (Co-Investigator (CoI)), Aichernig, B. (Co-Investigator (CoI)), Bösch, W. (Co-Investigator (CoI)), Baunach, M. C. (Co-Investigator (CoI)), Tappler, M. (Co-Investigator (CoI)), Malenko, M. (Co-Investigator (CoI)), Weiser, S. (Co-Investigator (CoI)), Eichlseder, M. (Co-Investigator (CoI)), Leitinger, E. (Co-Investigator (CoI)), Grosinger, J. (Co-Investigator (CoI)), Großwindhager, B. (Co-Investigator (CoI)), Ebrahimi, M. (Co-Investigator (CoI)), Alothman Alterkawi, A. B. (Co-Investigator (CoI)), Knoll, C. (Co-Investigator (CoI)), Teschl, R. (Co-Investigator (CoI)), Saukh, O. (Co-Investigator (CoI)), Rath, M. (Co-Investigator (CoI)), Steinberger, M. (Co-Investigator (CoI)), Steinbauer-Wagner, G. (Co-Investigator (CoI)) & Tranninger, M. (Co-Investigator (CoI))
1/01/16 → 31/03/22
Project: Research project