67 citations · 127 across the 9 of their papers we have counts for
10 papers
QoS-Aware Federated Learning for Multimodal In-Cabin Interaction in Smart Vehicles
Baran Can Gül, Mert Nakıp, Nasser Jazdi +1
Modern smart vehicles leverage multimodal sensors, ranging from high-bandwidth vision systems to low-rate physiological monitors, to provide personalized in-cabin services. However…
A Predictive Neural Network Architecture for Early Detection of Low-Rate Cyberattacks
Mert Nakıp
Low-Rate Denial of Service (LDoS) attacks pose a significant challenge to IoT networks due to their subtle and prolonged nature, often evading traditional intrusion detection syste…
Renewable energy management in smart home environment via forecast embedded scheduling based on Recurrent Trend Predictive Neural Network
Mert Nakıp, Onur Çopur, Emrah Biyik +1
Smart home energy management systems help the distribution grid operate more efficiently and reliably, and enable effective penetration of distributed renewable energy sources. The…
Online Self-Supervised Deep Learning for Intrusion Detection Systems
Mert Nakıp, Erol Gelenbe
This paper proposes a novel Self-Supervised Intrusion Detection (SSID) framework, which enables a fully online Deep Learning (DL) based Intrusion Detection System (IDS) that requir…
Decentralized Online Federated G-Network Learning for Lightweight Intrusion Detection
Mert Nakıp, Baran Can Gül, Erol Gelenbe
Cyberattacks are increasingly threatening networked systems, often with the emergence of new types of unknown (zero-day) attacks and the rise of vulnerable devices. Such attacks ca…
Measurement Based Evaluation and Mitigation of Flood Attacks on a LAN Test-Bed
Mohammed Nasereddin, Mert Nakıp, Erol Gelenbe
The IoT is vulnerable to network attacks, and Intrusion Detection Systems (IDS) can provide high attack detection accuracy and are easily installed in IoT Servers. However, IDS are…
Associated Random Neural Networks for Collective Classification of Nodes in Botnet Attacks
Erol Gelenbe, Mert Nakıp
Botnet attacks are a major threat to networked systems because of their ability to turn the network nodes that they compromise into additional attackers, leading to the spread of h…
Real-Time Cyberattack Detection with Offline and Online Learning
Erol Gelenbe, Mert Nakıp
This paper presents several novel algorithms for real-time cyberattack detection using the Auto-Associative Deep Random Neural Network, which were developed in the HORIZON 2020 IoT…
Engagement Detection with Multi-Task Training in E-Learning Environments
Onur Copur, Mert Nakıp, Simone Scardapane +1
Recognition of user interaction, in particular engagement detection, became highly crucial for online working and learning environments, especially during the COVID-19 outbreak. Su…
Curse of Small Sample Size in Forecasting of the Active Cases in COVID-19 Outbreak
Mert Nakıp, Onur Çopur, Cüneyt Güzeliş
During the COVID-19 pandemic, a massive number of attempts on the predictions of the number of cases and the other future trends of this pandemic have been made. However, they fail…