| 2021 | QRS | Curious SDN for network attack mitigation. | Mikhail Zolotukhin, Timo Hmlinen, Riku Immonen |
| 2020 | AINA | Linear Approximation Based Compression Algorithms Efficiency to Compress Environmental Data Sets. | Olli Vnnen, Mikhail Zolotukhin, Timo Hmlinen |
| 2020 | NetSoft | Reinforcement Learning for Attack Mitigation in SDN-enabled Networks. | Mikhail Zolotukhin, Sanjay Kumar, Timo Hmlinen |
| 2017 | NSS | Probabilistic Transition-Based Approach for Detecting Application-Layer DDoS Attacks in Encrypted Software-Defined Networks. | Elena Ivannikova, Mikhail Zolotukhin, Timo Hmlinen |
| 2016 | NOMS | On optimal placement of low power nodes for improved performance in heterogeneous networks. | Alexander Sayenko, Mikhail Zolotukhin, Timo Hmlinen |
| 2014 | DASC | Analysis of HTTP Requests for Anomaly Detection of Web Attacks. | Mikhail Zolotukhin, Timo Hmlinen, Tero Kokkonen, Jarmo Siltanen |
| 2014 | MSWIM | On optimal relay placement for improved performance in non-coverage limited scenarios. | Mikhail Zolotukhin, Alexander Sayenko, Timo Hmlinen |
| 2013 | GLOBECOM | Support vector machine integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware. | Mikhail Zolotukhin, Timo Hmlinen |
| 2012 | IWCMC | Online anomaly detection by using N-gram model and growing hierarchical self-organizing maps. | Mikhail Zolotukhin, Timo Hmlinen, Antti Juvonen |
| 2012 | WEBIST | Growing Hierarchical Self-organizing Maps and Statistical Distribution Models for Online Detection of Web Attacks. | Mikhail Zolotukhin, Timo Hmlinen, Antti Juvonen |
| 2012 | WEBIST | Growing Hierarchical Self-organising Maps for Online Anomaly Detection by using Network Logs. | Mikhail Zolotukhin, Timo Hmlinen, Antti Juvonen |