Panagiotis Bountakas

Orcid: 0000-0001-8155-1784

According to our database1, Panagiotis Bountakas authored at least 12 papers between 2021 and 2024.

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Bibliography

2024
Composite Inspection and Certification (CIC) System for Cybersecuity Assessment of ICT Products, Services, and Processes.
Proceedings of the IEEE International Conference on Cyber Security and Resilience, 2024

Uncovering Hidden Threats: Automated, Machine Learning-based Discovery & Extraction of Cyber Threat Intelligence from Online Sources.
Proceedings of the IEEE International Conference on Cyber Security and Resilience, 2024

SYNAPSE - An Integrated Cyber Security Risk & Resilience Management Platform, With Holistic Situational Awareness, Incident Response & Preparedness Capabilities: SYNAPSE.
Proceedings of the 19th International Conference on Availability, Reliability and Security, 2024

AIAS: AI-ASsisted cybersecurity platform to defend against adversarial AI attacks.
Proceedings of the 19th International Conference on Availability, Reliability and Security, 2024

2023
Defense strategies for Adversarial Machine Learning: A survey.
Comput. Sci. Rev., August, 2023

HELPHED: Hybrid Ensemble Learning PHishing Email Detection.
J. Netw. Comput. Appl., 2023

A Bring Your Own Device security awareness survey among professionals.
Proceedings of the 18th International Conference on Availability, Reliability and Security, 2023

Adversarial Machine Learning Attacks on Multiclass Classification of IoT Network Traffic.
Proceedings of the 18th International Conference on Availability, Reliability and Security, 2023

2022
EKnad: Exploit Kits' network activity detection.
Future Gener. Comput. Syst., 2022

GTM: Game Theoretic Methodology for optimal cybersecurity defending strategies and investments.
Proceedings of the ARES 2022: The 17th International Conference on Availability, Reliability and Security, Vienna,Austria, August 23, 2022

2021
NodeXP: NOde.js server-side JavaScript injection vulnerability DEtection and eXPloitation.
J. Inf. Secur. Appl., 2021

A Comparison of Natural Language Processing and Machine Learning Methods for Phishing Email Detection.
Proceedings of the ARES 2021: The 16th International Conference on Availability, 2021


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