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Publications

Publications

Zhou G, Liu Y, Yan Z, Gelenbe E. 2024. Is ChatGPT Trustworthy Enough? A Review. IEEE Consumer Electronics Magazine 2024.

Journal: IEEE Consumer Electronics Magazine, vol. 13, 2024 Authors: Zhou G, Liu Y, Yan Z, Gelenbe E. Abstract: ChatGPT, as an advanced model that seamlessly integrates into diverse digital interactions, shows great potential to enhance the performance of consumer technology and reshape its landscape. The critical question of its trustworthiness…
Publications

Siavvas M, Xanthopoulou G, Kalouptsoglou I, Kehagias D, Tzovaras D. 2024. Digital Transformation of Security Standards: Requirements Extraction using Large Language Models. DSA 2024.

Conference: 11th International Conference on Dependable Systems and Their Applications (DSA2024), 2-3. November 2024, Taicang, Suzhou, China Authors: Siavvas M, Xanthopoulou G, Kalouptsoglou I, Kehagias D, Tzovaras D. Abstract: Compliance with international security standards is essential for ensuring the security of information systems, and thereby their dependability and trustworthiness. Compliance…
Publications

Barakat R, Josten S, Schneider M. 2024. Buffer Access Monitoring for Enhanced Buffer Overflow Detection in Fuzzing. EuroCyberSec 2024.

Conference: EuroCyberSec 2024, 23. October 2024, Krakow, Poland Authors: Barakat R, Josten S, Schneider M. Abstract: Buffer overflows remain one of the most critical and widespread vulnerabilities in software systems. Traditional fuzzing techniques often lack the precision required to reliably detect buffer overflows. This paper presents BUFFERMONITOR, a novel approach…
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…
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…
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…
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,…
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…
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…