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Anna Marton, Safepay Systems

Siavvas M, Kalouptsoglou I, Gelenbe E, Kehagias D, Tzovaras D. 2024. Transforming the field of Vulnerability Prediction: Are Large Language Models the key? EuroCyberSec 2024. Publications

Siavvas M, Kalouptsoglou I, Gelenbe E, Kehagias D, Tzovaras D. 2024. Transforming the field of Vulnerability Prediction: Are Large Language Models the key? EuroCyberSec 2024.

Conference: EuroCyberSec 2024, 23. October 2024, Krakow, Poland Authors: Siavvas M, Kalouptsoglou I, Gelenbe E, Kehagias D, Tzovaras D. Abstract: Vulnerability prediction is an important mechanism for secure software development, as it enables the early identification and mitigation of software vulnerabilities. Vulnerability prediction models (VPMs) are machine learning (ML) models…
Anna Marton, Safepay Systems
October 23, 2024
The DOSS IoT Supply Trust Chain (STC) Concept Insights

The DOSS IoT Supply Trust Chain (STC) Concept

By András Vilmos, DOSS Project Coordinator The Supply Chain Security Challenge In today's interconnected world, businesses and individuals increasingly rely on IoT devices, software, and services from a variety of sources, making supply chain security critical. The complexity and opacity of modern supply chains, combined with the implicit trust placed…
Anna Marton, Safepay Systems
October 22, 2024
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

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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