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Data and Application Security

Team

Employee

Dr. Giovanni Apruzzese

Assistant Professor - Data and Application Security

Employee

Prof. Dr. Pavel Laskov

Professor - Data and Application Security Academic Director MSc IS - Liechtenstein Business School

Employee

Lazar Maksimovic

Student Assistant - Data and Application Security

Employee

Gloria Victoria Nachbaur BSc

Student Assistant - Data and Application Security

Employee

Irdin Pekaric PhD

Postdoc - Data and Application Security

Employee

Edah Pekaric BSc.

Student Assistant - Data and Application Security

Employee

Research Assistant / PhD Student - Data and Application Security

Employee

Rodion Vladimirov MSc

Research Assistant / PhD Student - Data and Application Security

Verkerken, M., D'hooge, L., Volckaert, B., De Turck, F., & Apruzzese, G. (2026). ConCap: Practical Network Traffic Generation for (ML- and) Flow-based Intrusion Detection Systems. Paper presented at the 4th IEEE Conference on Secure and Trustworthy Machine Learning, Technical University of Munich, Germany.

Vladimirov, R., & Laskov, P. (2025). Challenges of Predictive Beamforming Using Geographical Positioning: Insights from the DeepSense Dataset. Paper presented at the 16th edition of the IFIP Wireless and Mobile Networking Conference (IFIP WMNC), Leuven, Belgium.

Vladimirov, R., & Laskov, P. (2025). The Risk of Adversarial Perturbations for Deep Learning in Antenna Measurements. Paper presented at the 2025 IEEE Conference on Antenna Measurements and Applications (CAMA), Antibes Juan-les-Pins, France.

Pfister, M., Arpuzzese, G., & Pekaric, I. (2025). Department-Specific Security Awareness Campaigns: A Cross-Organizational Study of HR and Accounting. Paper presented at the APWG's 2025 Symposium on Electronic Crime Research (eCrime 2025), San Diego, USA.

Schröer, S., Pajola, L., Castagnaro, A., Apruzesse, G., & Conti, M. (2025). Exploiting AI for Attacks: On the Interplay between Adversarial AI and Offensive AI. IEEE Intelligent Systems.

Flores Comeca, A. L., Masarykova, N., Halinkovic, M., Galinski, M., Laskov, P., & Vinel, A. (2025). Social Robots for Road Safety: Pedestrian Crossing Assistance Use-Case. Paper presented at the International Symposium ELMAR.

Weinz, M., Zannone, N., Allodi, L., & Apruzesse, G. (2025). The Impact of Emerging Phishing Threats: Assessing Quishing and LLM-generated Phishing Emails against Organizations. Paper presented at the 20th ACM Asia Conference on Computer and Communications Security.

Pajola, L., Caripoti, E., Banzer, S., Pizzi, S., Conti, M., & Apruzzese, G. (2025). E-PhishGEN: Unlocking Novel Research in Phishing Email Detection. Paper presented at the 18 th ACM Workshop on Artificial Intelligence and Security, Taipei, Taiwan.

Schröer, S., Seideman, J. D., Shoufu, L., Apruzesse, G., Dietrich, S., & Laskov, P. (2025). Using a Stack to Find an AI Needle: Topic Modeling for Cyber Threat Intelligence. Digital Threats: Research and Practice, 6(4).

Rosenzweig, B., Dalla Valle, V., Apruzzese, Giovanni, & Fass, A. (2025). It's Not Easy: Applying Supervised Machine Learning to Detect Malicious Extensions in the Chrome Web Store. ACM Transactions on the Web.

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