$P^2$ESA : privacy-preserving environmental sensor-based authentication

Krašovec, Andraž (avtor), Baldini, Gianmarco (avtor), Pejović, Veljko (avtor)

The presence of Internet of Things (IoT) devices in modern working and living environments is growing rapidly. The data collected in such environments enable us to model users’ behaviour and consequently identify and authenticate them. However, these data may contain information about the user’s current activity, emotional state, or other aspects that are not relevant for authentication. In this work, we employ adversarial deep learning techniques to remove privacy-revealing information from the data while keeping the authentication performance levels almost intact. Furthermore, we develop and apply various techniques to offload the computationally weak edge devices that are part of the machine learning pipeline at training and inference time. Our experiments, conducted on two multimodal IoT datasets, show that P2ESA can be efficiently deployed and trained, and with user identification rates of between 75.85% and 93.31% (c.f. 6.67% baseline), can represent a promising support solution for authentication, while simultaneously fully obfuscating sensitive information.

• Jezik: Angleški jezik
• Ključne besede: behavioural authentication, edge computing, ubiquitous sensing
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FRI - Fakulteta za računalništvo in informatiko
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2025
• Št. strani: 20 str.
• Številčenje: Vol. 25, iss. 15, art. 4842
• PID: 20.500.12556/RUL-171169
• UDK: 004
• ISSN pri članku: 1424-8220
• DOI: 10.3390/s25154842
• COBISS.SI-ID: 245655043
• Datum objave v RUL: 14.08.2025

Gradivo je del revije

• Naslov: Sensors
• Skrajšan naslov: Sensors
• Založnik: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: vedenjska avtentikacija, robno računalništvo, vseprisotno zaznavanje

Projekti

• Financer: ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
• Številka projekta: N2-0393
• Naslov: Približno računanje za prilagodljivo porazdeljeno umetno inteligenco

• Financer: ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
• Številka projekta: J2-3047
• Naslov: Kontekstno-odvisno približno računanje na mobilnih napravah