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Publications

Maliga D, Nagy R, Buttyán L. 2024. A pipeline for processing large datasets of potentially malicious binaries with rate-limited access to a cloud-based malware analysis platform. EuroCyberSec 2024. Publications

Maliga D, Nagy R, Buttyán L. 2024. A pipeline for processing large datasets of potentially malicious binaries with rate-limited access to a cloud-based malware analysis platform. EuroCyberSec 2024.

Conference: EuroCyberSec 2024, 23. October 2024, Krakow, Poland Authors: Maliga D, Nagy R, Buttyán L. Abstract: In this paper, we present a pipeline that we designed for cleaning and processing large datasets of potentially malicious binaries using access to a rate-limited cloud-based malware analysis platform. Our goal is to efficiently…
Anna Marton
October 23, 2024
Kalouptsoglou I, Siavvas M, Ampatzoglou A, Kehagias D, Chatzigeorgiou A. 2024. Vulnerability prediction using pre-trained models: An empirical evaluation. EuroCyberSec 2024. Publications

Kalouptsoglou I, Siavvas M, Ampatzoglou A, Kehagias D, Chatzigeorgiou A. 2024. Vulnerability prediction using pre-trained models: An empirical evaluation. EuroCyberSec 2024.

Conference: EuroCyberSec 2024, 23. October 2024, Krakow, Poland Authors: Kalouptsoglou I, Siavvas M, Ampatzoglou A, Kehagias D, Chatzigeorgiou A. Abstract: The rise of Large Language Models (LLMs) has provided new directions for addressing downstream text classification tasks, such as vulnerability prediction, where segments of the source code are classified as…
Anna Marton
October 23, 2024
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
October 23, 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
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
October 5, 2024