dr. inż. Mert Nakip Email: Orcid ID: 0000-0002-6723-6494Stanowisko: adiunktZespół badawczy Zespół Modelowania, Oceny Efektywności i Bezpieczeństwa Systemów Komputerowych Horizontal TabsPublikacje Biblio RSS Submitted 1. Gelenbe, E., and M. Nakip, "Associated Random Neural Networks for Collective Classification of Nodes in Botnet Attacks", arXiv, Submitted. (1.86 MB) 2024 2. Nasereddin, M., M. Nakip, and E. Gelenbe, "Deep Learning Intrusion Detection and Mitigation of DoS Attacks", 32nd International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS24), Krakow, Poland, IEEE, 2024. (2.84 MB) 3. Nakip, M., B. Can Gül, and E. Gelenbe, "Decentralized Online Federated G-Network Learning for Lightweight Intrusion Detection", Modeling, Analysis, and Simulation On Computer and Telecommunication Systems (MASCOTS): IEEE, 2024. (1.06 MB) 4. Nakip, M., and E. Gelenbe, "Online Self-Supervised Deep Learning for Intrusion Detection Systems", IEEE Transactions on Information Forensics and Security, vol. 19, 05/2024 . (6.97 MB) 5. Bulucu, P., M. Nakip, and C. Güzeliş, "Multi-Sensor E-Nose based on Online Transfer Learning Trend Predictive Neural Network", IEEE Access, 2024. (3.93 MB) 6. Nakip, M., N. Kelesoglu, and C. Güzeliş, "Fire Detection and Risk Assessment via Support Vector Regression with Flattening-Samples Based Augmented Regularization", Applied Soft Computing, vol. 164, 10/2024. 7. Gelenbe, E., M. Nakip, and M. Siavvas, "System-wide vulnerability of multi-component software", Computers & Industrial Engineering, vol. 196, 10/2024. 8. Gelenbe, E., B. Can Gül, and M. Nakip, "DISFIDA: Distributed Self-Supervised Federated Intrusion Detection Algorithm with Online Learning for Health Internet of Things and Internet of Vehicles ", Internet of Things, vol. 28, 12/2024. (2.17 MB) 9. Gelenbe, E., M. Nakip, and M. Siavvas, "System Wide Vulnerability and Trust in Multi-Component Communication System Software", IEEE Network, 2024. (3.98 MB) 2023 10. Gelenbe, E., and M. Nakip, "IoT Network Cybersecurity Assessment with the Associated Random Neural Network", IEEE Access, 2023. (966.17 KB) 11. Nasereddin, M., M. Nakip, and E. Gelenbe, "Measurement Based Evaluation and Mitigation of Flood Attacks on a LAN Test-Bed", The 48th IEEE Conference on Local Computer Networks, Daytona Beach, Florida, USA, IEEE, 2023. (861.42 KB) 12. Nakip, M., O. Çopur, E. Biyik, and C. Güzeliş, "Renewable energy management in smart home environment via forecast embedded scheduling based on Recurrent Trend Predictive Neural Network", Applied Energy, vol. 340, 03/2023. (887.88 KB) 13. Gelenbe, E., and M. Nakip, "Real-Time Cyberattack Detection with Offline and Online Learning", IEEE International Symposium on Local and Metropolitan Area Networks, London, United Kingdom, IEEE, 2023. (1.09 MB) 2022 14. Gelenbe, E., M. Nakip, and T. Czachórski, "Improving Massive Access to IoT Gateways", Performance Evaluation, 08/2022. 15. Gelenbe, E., and M. Nakip, "Traffic Based Sequential Learning During Botnet Attacks to Identify Compromised IoT Devices", IEEE Access, vol. 10, 10/2022. (1.74 MB) 16. Nakip, M., A. Helva, C. Güzeliş, and V. Rodoplu, "MOSAL: A Subspace Based Forecasting Algorithm for Throughput Maximization in IoT Networks", IEEE Sensors Journal, 11/2022. 17. Gelenbe, E., and M. Nakip, "G-Networks Can Detect Different Types of Cyberattacks", 2022 Mascots: 30th International Symposium on the Modelling, Analysis and Simulation of Computer and Telecommunication Systems, Nice, France, IEEE, 2022. (1.51 MB) 18. Dayı, A. Kerem, V. Rodoplu, M. Nakip, B. Pehlivan, and C. Güzeliş, "Multi-Channel Subset Iteration with Minimal Loss in Available Capacity (MC-SIMLAC) Algorithm for Joint Forecasting-Scheduling in the Internet of Things", Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA), vol. 13, issue 2, 06/2022. 19. Nakip, M., B. Can Gül, V. Rodoplu, and C. Güzeliş, "Predictability of Internet of Things Traffic at the Medium Access Control Layer Against Information-Theoretic Bounds", IEEE Access, vol. 10, 05/2022. 20. Siavvas, M., E. Gelenbe, D. Tsoukalas, I. Kalouptsoglou, M. Mathioudaki, M. Nakip, D. Kehagias, and D. Tzovaras, "The IoTAC Software Security-by-Design Platform: Concept, Challenges, and Preliminary Overview", 18th International Conference on the Design of Reliable Communication Networks (DRCN), Vilanova i la Geltrú, Spain, IEEE, 2022. (1.33 MB) 21. Nakip, M., and E. Gelenbe, "Botnet Attack Detection with Incremental Online Learning", EuroCybersec 2021, Nice, France, Springer, 2022. 22. Gelenbe, E., M. Nakip, D. Marek, and T. Czachórski, "Mitigating the Massive Access Problem in the Internet of Things", EuroCybersec, Nice, France, Springer, 2022. 23. Çopur, O., M. Nakip, S. Scardapane, and J. Slowack, "Engagement Detection with Multi-Task Training in E-Learning Environments", International Conference on Image Analysis and Processing (ICIAP): Springer, 2022. (1.2 MB) 24. Nakip, M., E. Çakan, V. Rodoplu, and C. Güzeliş, "Dynamic Automatic Forecaster Selection via Artificial Neural Network Based Emulation to Enable Massive Access for the Internet of Things", Journal of Network and Computer Applications (JNCA), 2022. (1.36 MB) 2021 25. Nakip, M., C. Güzeliş, and O. Yıldız, "Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection", IEEE Access, vol. 9, 10/2021. (1.86 MB) Strony12następna ›ostatnia »
