activity
20222025
most citedOnline Self-Supervised Deep Learning for Intrusion Detection Systems

67 citations · 81 across the 11 of their papers we have counts for

collaborators

11 papers

cs.NI2025★ 5 cited

IoT Performance for Maritime Passenger Evacuation

Yuting Ma, Erol Gelenbe, Kezhong Liu

The safe and swift evacuation of passengers from Maritime Vessels, requires an effective Internet of Things(IoT) as well as an information and communication technology(ICT) infrast…

cs.NI2025

Adaptive Attack Mitigation for IoV Flood Attacks

Erol Gelenbe, Mohammed Nasereddin

Gateway Servers for the Internet of Vehicles (IoV) must meet stringent Security and Quality of Service (QoS) requirements, including cyberattack protection, low delays and minimal…

cs.NI2025

Attack Mitigation in Gateways of Pervasive Systems

Erol Gelenbe, Mohammed Nasereddin

In pervasive systems, mobile devices and other sensors access Gateways, which are Servers that communicate with the devices, provide low latency services, connect them with each ot…

cs.NI2023

Impact of Network Delay and Decision Imperfections in IoT Assisted Cruise Ship Evacuation

Yuting Ma, Erol Gelenbe, Kezhong Liu

Major challenges of assisting passengers to safely and quickly escape from ships when an emergency occurs, include complex realistic features such as human behavior uncertainty, dy…

cs.CR2023

Protecting IoT Servers Against Flood Attacks with the Quasi Deterministic Transmission Policy

Erol Gelenbe, Mohammed Nasereddin

IoT Servers that receive and process packets from IoT devices should meet the QoS needs of incoming packets, and support Attack Detection software that analyzes the incoming traffi…

cs.CR2023★ 67 cited

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…

cs.CR2023★ 1 cited

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…

cs.CR2023

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…

cs.NI2023★ 1 cited

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…

cs.CR2023

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…

quant-ph2022★ 7 cited

Random Quantum Neural Networks (RQNN) for Noisy Image Recognition

Debanjan Konar, Erol Gelenbe, Soham Bhandary +2

Classical Random Neural Networks (RNNs) have demonstrated effective applications in decision making, signal processing, and image recognition tasks. However, their implementation h…