Enhancing Keyless Entry with Anomaly-Based Two-Factor Authentication for Improved User Convenience

Dhanve, Avadhoot Prashant (2025) Enhancing Keyless Entry with Anomaly-Based Two-Factor Authentication for Improved User Convenience. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (4MB) | Preview
Preview	PDF (Configuration Manual) Download (1MB) | Preview

Abstract

Modern vehicles with keyless entry systems remain critically vulnerable to sophisticated cyberattacks, with 93% of stolen vehicles recovered in 2023 involving keyless entry exploits and automotive cybersecurity incidents reaching 215 cases in 2024 alone, resulting in tens of billions of dollars in estimated damages. Traditional multi-factor authentication (MFA) solutions impose significant usability penalties, with studies reporting user dissatisfaction with always-on 2FA systems due to authentication delays ranging from 2.3 to 4.1 seconds. This research investigates an adaptive MFA framework that conditionally activates two-factor authentication only when device anomalies are detected through MAC address verification. The prototype system was implemented using two Raspberry Pi units communicating via infrared signals, with A MAC address protection and TOTP-based secondary authentication. Performance evaluation under controlled laboratory conditions demonstrated near-perfect accuracy in distinguishing between registered and unregistered devices though real-world variability and environmental noise may affect performance. Encryption operations completed in an average of 0.000976 seconds, with system resource utilization remaining minimal, even during peak authentication processes. The adaptive approach reduced authentication friction by 100% during normal operation while maintaining robust security through conditional 2FA activation, achieving maximum effectiveness in preventing unauthorized access when anomalies were detected. This research addresses the question: ”How can adaptive multi-factor authentication (MFA) balance security and usability in automotive keyless entry systems?”. To the best of my knowledge, this is the first working prototype that integrates MAC-anomaly detection with adaptive 2FA in an IR-based keyless entry simulation for automotive systems, demonstrating that adaptive authentication can effectively solve the security-versus-usability problem, which has been a major obstacle to using multi-factor authentication (MFA) in vehicle access control systems. While some studies have proposed anomaly-triggered authentication mechanisms, none have demonstrated a lightweight, MAC-driven prototype tailored to vehicle access control.

Item Type:	Thesis (Masters)
Supervisors:	Name Email McLaughlin, Eugene UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	17 Aug 2026 14:21
Last Modified:	17 Aug 2026 14:21
URI:	https://norma.ncirl.ie/id/eprint/9528

Actions (login required)

View Item