A Comprehensive Review on Secure Biometric-Based Continuous Authentication and User Profiling
Open accessAbstract
Authentication systems are pivotal in fortifying security measures against unauthorized access. Yet, they often fall short of effectively combating impersonation attacks, leaving systems susceptible to exploitation. Continuous Authentication Systems (CAS) have emerged as a promising solution, offering dynamic adaptability to evolving threats. However, the existing literature lacks a thorough critical evaluation of CAS progress, hindering practical advancements in the field. This comprehensive review addresses this gap by analyzing recent advancements, emerging trends, and critical challenges in CAS design and implementation. The review reveals that while supervised learning methods, particularly score-level fusion, dominate CAS classification techniques, there remains a dearth of comparative analysis regarding the efficacy of different biometric pairings (e.g., physiological, behavioral, or multimodal). While studies predominantly assess CAS accuracy using metrics like False Rejection Rate (FRR), False Acceptance Rate (FAR), and Equal Error Rate (EER), aspects crucial to practical success, such as usability, security, and scalability, often receive inadequate attention. Moreover, the practical viability of CAS demands comprehensive implementation and evaluation using real-world data. This survey paper explores various facets of CAS, including physiological and behavioral biometrics, multimodal biometrics, context-aware techniques, and other emerging methodologies. Additionally, open issues, challenges, and proposed future directions aim to inspire further research and development in secure biometric-based continuous authentication and user profiling.
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Ayeswarya and Singh provide an up-to-date review of continuous authentication and user profiling, noting the growing focus on behavioural signals that can operate passively without interrupting the user.
“Ayeswarya and Singh [32] provide an up-to-date review of continuous authentication and user profiling, noting the growing focus on behavioural signals that can operate passively without interrupting the user.”
From A SIEM-Integrated Cybersecurity Prototype for Insider Threat Anomaly Detection Using Enterprise Logs and Behavioural Biometrics (2026) · cites this paper as [32]
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Physical-Unclonable-Function-Based Secure and Anonymous User Authentication for Smart Homes
Garapati, R. S., Paleti, S., Meda, R., Nagabhyru, K. C., & Priya, B. S. D. (2026) · Lecture notes in electrical engineering · doi:10.1007/978-3-032-20235-2_33 · Cited by 6 · see citing works
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Post-quantum zero-knowledge blockchain-enabled for federated IoT security
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Security and Usability Trade-offs in User Authentication Systems: A Review and Analytical Framework
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- Authors
- Ayeswarya, S., & Singh, K. J.
- Affiliations
- Vellore Institute of Technology University (IN)
- Venue
- IEEE Access
- Published
- 2024
- Volume
- 12
- Pages
- 82996-83021
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W4399485312
- Cited by
- 66
- References
- 166
- Citations by year
- 2026: 36 · 2025: 25 · 2024: 5
- FWCI
- 24.89
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- IEEE Access (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Physical Sciences › Computer Science › Computer Networks and Communications › Advanced Authentication Protocols Security
- Keywords
- continuous authentication, biometric authentication, user profiling, impersonation attacks, score-level fusion, physiological biometrics, behavioral biometrics, multimodal biometrics, context-aware authentication, false acceptance rate, false rejection rate, equal error rate, usability, scalability
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