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Peyman Kabiri

Dr. Peyman Kabiri Ph.D, M.Sc, B.Eng

Senior Lecturer

Summary

I joined Sheffield Hallam University from September 2018. I am module leader for the Network Intrusion Detection (NID) module.

My university teaching experience as a Ph.D. holder started in 2000, and I have lectured several computer science subject areas. I have supervised projects of both undergraduate and postgraduate students.

I have been involved in cybersecurity research for around 15 years.

  • About

    I received my Ph.D. in Computing from The Nottingham Trent University in 2000. Since then I have been researching and teaching at universities.

    I started research in cybersecurity from 2004.

    I use my research results to teach students and aim to always provide them with up-to-date insight. This is especially helpful with newer subject areas where good books are hard to find and changes in the field are significant.

    My approach to solved research problems is based on data analysis and machine learning methods.

    Since 2010, I have been teaching in the areas of Network Intrusion Detection and Response and System Security. I have successfully graduated 3 Ph.D., 45 M.Sc. and 11 B.Eng. students up to 2018 (both jointly and on my own).

    I am regularly invited to act as referee for academic journals and conferences.

    I believe in thinking out of the box and to seek suitable solutions to real-life problems in even unconventional places.

  • Teaching

    Network Intrusion Detection

  • Publications

    Journal articles

    Aghdam, M.H., Analoui, M., & Kabiri, P. (2017). Collaborative filtering using non-negative matrix factorisation. Journal of Information Science, 43 (4), 567-579. http://doi.org/10.1177/0165551516654354

    Nejat, S.K., & Kabiri, P. (2017). An adaptive and cost-based intrusion response system. Cybernetics and Systems, 48 (6-7), 495-509. http://doi.org/10.1080/01969722.2017.1319693

    Moshki, M., Kabiri, P., & Mohebalhojeh, A. (2017). Scalable data-driven modeling of spatio-temporal systems: Weather forecasting. Intelligent Data Analysis, 21 (3), 577-595. http://doi.org/10.3233/IDA-150494

    Aghdam, M.H., & Kabiri, P. (2016). Feature selection for intrusion detection system using ant colony optimization. International Journal of Network Security, 18 (3), 420-432

    Rahimizadeh, K., & Kabiri, P. (2014). Trust-based routing method using a mobility-based clustering approach in mobile ad hoc networks. Security and Communication Networks, 7 (11), 1746-1763. http://doi.org/10.1002/sec.872

    Kabiri, P., & Aghaei, M. (2011). Feature analysis for intrusion detection in mobile Ad-hoc networks. International Journal of Network Security, 12 (1), 42-49

    Kabiri, P., & Ghorbani, A.A. (2007). A rule-based temporal alert correlation system. International Journal of Network Security, 5 (1), 66-72

    Conference papers

    Kianinejad, M., & Kabiri, P. (2018). A strategy for trust propagation along the more trusted paths. In 3rd Conference on Swarm Intelligence and Evolutionary Computation, CSIEC 2018, 1-6. IEEE: http://doi.org/10.1109/CSIEC.2018.8405406

    Hoseini, S.A., & Kabiri, P. (2017). A feature-based approach for monocular camera tracking in unknown environments. In 3rd International Conference on Pattern Analysis and Image Analysis, IPRIA 2017, 75-79. http://doi.org/10.1109/PRIA.2017.7983021

    Zargar, G.R., & Kabiri, P. (2010). Selection of effective network parameters in attacks for intrusion detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6171 LNAI, 643-652. http://doi.org/10.1007/978-3-642-14400-4_50

    Zargar, G.R., & Kabiri, P. (2009). Identification of effective network features to detect smurf attacks. In SCOReD2009 - Proceedings of 2009 IEEE Student Conference on Research and Development, 49-52. http://doi.org/10.1109/SCORED.2009.5443345

    Zargar, G.R., & Kabiri, P. (2009). Identification of effective network features for probing attack detection. In 2009 1st International Conference on Networked Digital Technologies, NDT 2009, 392-397. http://doi.org/10.1109/NDT.2009.5272124

    Kabiri, P., Shahbazi, H., & Soryani, M. (2008). Statistical shape based multispectral image retrieval extracting power spectrum vectors. In 3rd International Conference on Digital Information Management, ICDIM 2008, 650-655. http://doi.org/10.1109/ICDIM.2008.4746804

    Shahbazi, H., Kabiri, P., & Soryani, M. (2008). Content based multispectral image retrieval using Independent Component Analysis. In Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008, 2, 485-489. http://doi.org/10.1109/CISP.2008.642

    Ahmadian, K., Golestani, A., Mozayani, N., Kabiri, P., & IEEE, (2007). A new multi-objective evolutionary approach for creating ensemble of classifiers. In 2007 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-8, 876-881.

    Ahmadian, K., Golestani, A., Mozayani, N., & Kabiri, P. (2007). A new multi-objective evolutionary approach for creating ensemble of classifiers. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 1031-1036. http://doi.org/10.1109/ICSMC.2007.4413723

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