1. 2017
  2. Learning behavioral fingerprints from Netflows using Timed Automata

    Pellegrino, N., Lin, Q., Hammerschmidt, C. & Verwer, S., 24 Jul 2017, 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). Chemouil, P., Monteiro, E., Charalambides, M., Madeira, E., Simoes, P., Secci, S., Gaspary, L. P. & dos Santos, C. R. P. (eds.). IEEE, p. 308-316 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  3. Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms

    Hammerschmidt, C. A., State, R. & Verwer, S., 2017, ArXiv Preprint. Vol. abs/1707.09430.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientific

  4. Reliable Machine Learning for Networking: Key Issues and Approaches

    Hammerschmidt, C. A., Garcia, S., Verwer, S. & State, R., 2017, 2017 IEEE 42nd conference on Local Computer Networks, LCN 2017. IEEE, p. 167-170 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  5. flexfringe: A Passive Automaton Learning Package

    Verwer, S. & Hammerschmidt, C. A., 2017, 2017 IEEE International Conference on Software Maintenance and Evolution, ICSME 2017. O'Conner, L. (ed.). Piscataway: IEEE, p. 638-642 5 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  6. 2016
  7. Behavioral Clustering of Non-Stationary IP Flow Record Data

    Hammerschmidt, C., Marchal, S., State, R. & Verwer, S., Nov 2016, 12th International Conference on Network and Service Management CNSM 2016. Piscataway, NJ: IEEE, p. 253-257 5 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  8. Efficient Learning of Communication Profiles from IP Flow Records

    Hammerschmidt, C., Marchal, S., State, R., Pellegrino, N. & Verwer, S., 2016, Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016. Kellenberger, P. (ed.). Los Alamitos, CA: IEEE, p. 1-4 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  9. Flexible State-Merging for learning (P)DFAs in Python

    Hammerschmidt, C., Loos, B., State, R., Engel, T. & Verwer, S., 2016, Proceedings of The 13th International Conference on Grammatical Inference: The JMLR Workshop and Conference, The Sequence PredictIction ChallengE (SPiCe). Verwer, S., van Zaanen, M. & Smetsers, R. (eds.). JMLR, Vol. 57. p. 154-159 6 p. (JMLR: Workshop and Conference Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  10. Learning Deterministic Finite Automata from Innite Alphabets

    Pellegrino, N., Hammerschmidt, C., Verwer, S. & Lin, Q., 2016, Proceedings of The 13th International Conference on Grammatical Inference: The JMLR Workshop and Conference, The Sequence PredictIction ChallengE (SPiCe). Verwer, S., van Zaanen, M. & Smetsers, R. (eds.). JMLR, Vol. 57. p. 69-72 5 p. (JMLR: Workshop and Conference Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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