Dr Francisco J. Aparicio Navarro

Dr Aparicio Navarro works as a Lecturer in Cyber Security at De Montfort University. His research interest are in the areas of Network Security, Intrusion Detection and Network Traffic Analysis. He is also a Certified Ethical Hacker / Penetration Tester. Dr Aparicio Navarro has advanced the state-of-the-art of network security by developing novel unsupervised Intrusion Detection Systems, and proposing statistical approaches to integrate Contextual Information and Situational Awareness into the cyber-attack detection process. He was involved in the defence project UDRC, collaborating with the MoD/Dstl, has delivered cyber security solutions for Connected Autonomous Vehicles, in partnership with Airbus, and researches methods to detect Advanced Persistent Threats and Multi-Stage Attacks in networked environments. Dr Aparicio Navarro is currently an Academic Visitor within the Signal Processing and Networks Research Group at Loughborough University.

Research Skills / Expertise:

• Computer Networks (Routing and Switching, CCNA)
• Anomaly-based & Signature-based Intrusion Detection Systems
• Penetration Testing & Ethical Hacking (CSTA)
• Data Mining & Machine Learning
• Network Traffic Monitoring, Cross-Layer Measurements & Data Fusion
• Context & Knowledge Representation

Full list of publications in Google Scholar

Selected Publications:

D. Kosmanos, A. Pappas, F. J. Aparicio-Navarro, L. Maglaras, H. Janicke, E. Boiten, A. Argyriou, "Intrusion detection system for platooning connected autonomous vehicles," in South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), 2019, pp. 1-9, to be published.

I. Ghafir, K. Kyriakopoulos, S. Lambotharan, F. J. Aparicio-Navarro, B. AsSadhan, H. BinSalleeh, D. M. Diab, “Hidden markov models and alert correlations for the prediction of advanced persistent threats,” in IEEE Access, vol. 7, 2019, pp. 99508-99520.

F. J. Aparicio-Navarro, K. Kyriakopoulos, I. Ghafir, S. Lambotharan, J. Chambers, “Multi-stage attack detection using contextual information,” in IEEE Military Communications Conference (MILCOM), 2018, pp. 920-925.

I. Ghafir, M. Hammoudeh, V. Prenosil, L. Han, R. Hegarty, K. Rabie, F. J. Aparicio-Navarro, “Detection of advanced persistent threat using machine-learning correlation analysis,” Elsevier Future Generation Computer Systems, vol. 89, 2018, pp. 349-359.

F. J. Aparicio-Navarro, K. Kyriakopoulos, Y. Gong, D. Parish, J. Chambers, “Using pattern-of-life as contextual information for anomaly-based intrusion detection systems,” IEEE Access, vol. 5, 2017, pp. 22177-22193. 

D. Santoro, G. Escudero-Andreu, K. Kyriakopoulos, F. J. Aparicio-Navarro, D. Parish, M. Vadursi, “A hybrid intrusion detection system for virtual jamming attacks on wireless networks,” Elsevier Measurement, vol. 109, 2017, pp. 79-87.

Network Security, Intrusion Detection Systems, Network Traffic Analysis, Computer Networks

19/20 Penetration Testing:

CTEC2914 - Penetration testing

CTEC5804 - Penetration Testing & Incident Response

18/19 Computer Networks:

CTEC3605 - Multi-Service Networks 1

CTEC3606 - Multi-Service Networks 2

Ethical Hacking - Certified Security Testing Associate (CSTA), 7Safe PA Consulting

• INSURE: Intrusion Detection System for Public Hotspot Cyber Security (Innovate UK) - 30694 - (Principal Investigator)

Previous projects:

• FLOURISH: Empowerment through Trusted Secure Mobility (Innovate UK & Airbus)
• Signal Processing Solutions for the Networked Battlespace (Dstl & EPSRC) - EP/K014307/1 & EP/K014307/2 (Research Associate)
• Cross Layer Techniques for Intrusion Tolerant Networks (EPSRC) - EP/H005005/1 (PhD Student)

Programme Committee:

Program Chair - 3rd IEEE Symposium on Software Engineering for Smart Systems (SSESS) 2019, Leicester, UK

Invited Speaker:

Workshop on Machine Learning for Cyber Security (2019), Loughborough University, Loughborough, UK

Faculty of Technology Research Seminar Series (2018), De Montfort University, Leicester, UK

Workshop in Cybersecurity and Future Challenges (2018), King Saud University, Riyadh, Saudi Arabia

Data Science and Signal Processing meeting (2017), The Alan Turing Institute, London, UK

Workshop in Anomaly Detection (2016), ANII, Montevideo, Uruguay