Our research focuses on securing IoT systems across smart homes, healthcare, and industrial environments. We develop innovative solutions to address emerging threats and privacy challenges in connected ecosystems.
Selected peer-reviewed papers, demos, and workshop publications related to IoT security in smart homes, healthcare, and industrial environments.
M. Alhussan, F. Boem, S. Ghoreishizadeh, A. M. Mandalari
Venue: Proc. 2025 IEEE International Symposium on Circuits and Systems (ISCAS)
Yash Vekaria, Aurelio Loris Canino, Jonathan Levitsky, Alex Ciechonski, Patricia Callejo, Anna Maria Mandalari, Zubair Shafiq
Venue: 34th USENIX Security Symposium
A. Losty, A. M. Mandalari, A. K. Mishra, M. Cunche
Venue: ANRW 2025 (Applied Networking Research Workshop)
Palmese, Fabio ; Mandalari, Anna Maria ; Haddadi, Hamed ; Enrico Cesare Redondi, Alessandro
Link: arXiv PDF
Aurelio Loris Canino, Gianluca Lax
Link: Springer
M. Alhussan, F. Boem, S. Ghoreishizadeh, A. M. Mandalari
Venue: Proc. IEEE BioSensors Conference (2024)
M. Alhussan, F. Boem, S. Ghoreishizadeh, A. M. Mandalari
Venue: 21st Intl. Conf. on Embedded Wireless Systems and Networks (EWSN)
M. Alhussan, F. Boem, S. Ghoreishizadeh, A. M. Mandalari
Venue: PhD School at EWSN (2024)
A. Losty, A. M. Mandalari
Venue: PhD School at EWSN (2024)

Mapping resilient communication solutions against adversarially-imposed network shutdowns.
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Developing intra-body communication (IBC) as a secure alternative to vulnerable BLE in medical wearables, addressing sniffing/MITM/DoS risks while maintaining clinical functionality
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TwinGuard is an adaptive digital twin system for real-time HTTP(S) intrusion detection. It combines trie-based path modeling, behavioral fingerprinting, and machine learning to detect evolving threats with 90% accuracy. Key features include dynamic retraining, attacker infrastructure profiling, and granular traffic analysis—revealing attack origins, tools, and strategies.
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