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Anna Marton, Safepay Systems

Nakip M, Gelenbe E. 2024. An Associated Random Neural Network Detects Intrusions and Estimates Attack Graphs. EuroCyberSec 2024. Publications

Nakip M, Gelenbe E. 2024. An Associated Random Neural Network Detects Intrusions and Estimates Attack Graphs. EuroCyberSec 2024.

Conference: EuroCyberSec 2024, 23. October 2024, Krakow, Poland Authors: Nakip M, Gelenbe E. Abstract: Cyberattacks, especially Botnet Distributed Denial of Service (DDoS), increasingly target networked systems, compromise interconnected nodes by constantly spreading malware. In order to prevent these attacks in their early stages, which includes stopping the spread of malware,…
Anna Marton, Safepay Systems
October 5, 2024
Nasereddin M, Nakip M, Gelenbe E. 2024. A Deep Learning based Intrusion Detection and Prevention System for Mitigating DoS Attacks. EuroCyberSec2024 Publications

Nasereddin M, Nakip M, Gelenbe E. 2024. A Deep Learning based Intrusion Detection and Prevention System for Mitigating DoS Attacks. EuroCyberSec2024

Conference: EuroCyberSec 2024, 23. October 2024, Krakow, Poland Authors: Nasereddin M, Nakip M, Gelenbe E. Abstract: Internet of Things (IoT) networks are highly vulnerable to network attacks, the most common examples being DoS and DDoS attacks. Those attacks flood the limited system resources of IoT devices and overwhelm networks with…
Anna Marton, Safepay Systems
October 5, 2024
Ma Y, Gelenbe E, Liu K. 2024. IoT Performance for Maritime Passenger Evacuation. WF-IoT 2024. Publications

Ma Y, Gelenbe E, Liu K. 2024. IoT Performance for Maritime Passenger Evacuation. WF-IoT 2024.

Conference: WF-IoT 2024, 10-13. November 2024, Ottawa, Canada Authors: Ma Y, Gelenbe E, Liu K. Abstract: 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) infrastructure. However, during emergencies, delays in IoT and…
Anna Marton, Safepay Systems
October 3, 2024
Automatic Vulnerability Categorization: Are Large Language Models (LLMs) the solution? Insights

Automatic Vulnerability Categorization: Are Large Language Models (LLMs) the solution?

By Miltiadis Siavvas,  Information Technologies Institute (ITI) of the Centre for Research and Technology-Hellas (CERTH) Problem Statement The early identification and mitigation of software vulnerabilities is critical for the development of secure software. To facilitate the vulnerability identification and mitigation process, several tools and techniques have been proposed over the…
Anna Marton, Safepay Systems
September 25, 2024
Bergquist J, Gelenbe E, Sigman K. 2024. On an Adaptive-Quasi-Deterministic Transmission Policy Queueing Model. MASCOTS 2024 Publications

Bergquist J, Gelenbe E, Sigman K. 2024. On an Adaptive-Quasi-Deterministic Transmission Policy Queueing Model. MASCOTS 2024

Conference: MASCOTS 2024 Authors: Bergquist J, Gelenbe E, Sigman K. Abstract: We analyze, further and deeper, a recently proposed technique for addressing the Massive Access Problem (MAP), an issue in telecommunications which arises when too many devices transmit packets to a gateway in quick succession. This technique, the Adaptive-Quasi-Deterministic Transmission…
Anna Marton, Safepay Systems
September 24, 2024
Gelenbe E, Nakip M, Siavvas M. 2024. System-Wide Vulnerability and Trust in Multi-Component Communication System Software. IEEE Network. 2024. Publications

Gelenbe E, Nakip M, Siavvas M. 2024. System-Wide Vulnerability and Trust in Multi-Component Communication System Software. IEEE Network. 2024.

Journal: IEEE Network. 2024. Authors: Gelenbe E, Nakip M, Siavvas M. Abstract: In the software rich environment of 6G, systems will be surrounded by edge devices that support distributed software systems which are critical to operations. Such systems may also be subject to frequent updates or uploads of individual software…
Anna Marton, Safepay Systems
September 13, 2024

This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101120270 – DOSS.

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