Enhancing Security in Digital Wallets Using Multi-Factor Authentication and Behavioral Biometrics

Authors

  • Sherin Riyana Independent Researcher, India. Author

DOI:

https://doi.org/10.56472/ICCSAIML25-162

Keywords:

Digital Wallet Security, Multi-Factor Authentication (MFA), Behavioral Biometrics, Continuous Authentication, Cybersecurity, Mobile Wallets, Authentication Technologies, Fraud Prevention, Secure Transactions

Abstract

Digital wallets have become a cornerstone of the modern financial ecosystem, providing users with a convenient and efficient means of conducting transactions. However, as digital wallets store sensitive personal and financial information, they are prime targets for cyberattacks and fraud. Traditional security measures, such as passwords and PINs, are no longer sufficient to prevent unauthorized access. This paper explores the potential of Multi-Factor Authentication (MFA) and Behavioral Biometrics in enhancing the security of digital wallets. MFA, which requires users to provide multiple forms of verification, offers an added layer of protection against unauthorized access. Behavioral Biometrics, which analyzes patterns in user behavior (e.g., keystroke dynamics, touch patterns), provides continuous authentication, further strengthening security. By integrating these two technologies, digital wallets can offer a more secure, user-friendly alternative to traditional authentication methods. The paper also addresses the challenges and privacy concerns associated with these technologies and explores future trends in digital wallet security

Downloads

Download data is not yet available.

References

[1] “The results indicate that biometric-based MFA significantly enhances security, reduces fraud, and improves user experience. However, challenges related to privacy concerns, data protection regulations, and technological limitations persist.”

[2] Bhagath Chandra Chowdari Marella, “Driving Business Success: Harnessing Data Normalization and Aggregation for Strategic Decision-Making”, International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, vol. 10, no.2, pp. 308 – 317, 2022. https://ijisae.org/index.php/IJISAE/issue/view/87

[3] Puvvada, R. K. "Optimizing Financial Data Integrity with SAP BTP: The Future of Cloud-Based Financial Solutions." European Journal of Computer Science and Information Technology 13.31 (2025): 101-123.

[4] Kirti Vasdev. (2020). “GIS in Cybersecurity: Mapping Threats and Vulnerabilities with Geospatial Analytics”. International Journal of Core Engineering & Management, 6(8, 2020), 190–195. https://doi.org/10.5281/zenodo.15193953

[5] Muniraju Hullurappa, Sudheer Panyaram, “Quantum Computing for Equitable Green Innovation Unlocking Sustainable Solutions,” in Advancing Social Equity Through Accessible Green Innovation, IGI Global, USA, pp. 387- 402, 2025.

[6] L. N. Raju Mudunuri, P. K. Maroju and V. M. Aragani, "Leveraging NLP-Driven Sentiment Analysis for Enhancing Decision-Making in Supply Chain Management," 2025 Fifth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), Bhilai, India, 2025, pp. 1-6, doi: 10.1109/ICAECT63952.2025.10958844.

[7] “Unlike conventional methods, behavioral biometrics leverage unique, continuous patterns in user behavior, making them difficult to replicate or steal. This paper explores the potential of behavioral biometrics as a supplementary factor in MFA, evaluating its effectiveness in enhancing security, reducing fraud, and improving user convenience.”

[8] Bhagath Chandra Chowdari Marella, “Scalable Generative AI Solutions for Boosting Organizational Productivity and Fraud Management”, International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, vol. 11, no.10, pp. 1013–1023, 2023.

[9] Sudheer Panyaram, Muniraju Hullurappa, “Data-Driven Approaches to Equitable Green Innovation Bridging Sustainability and Inclusivity,” in Advancing Social Equity Through Accessible Green Innovation, IGI Global, USA, pp. 139-152, 2025.

[10] RK Puvvada . “SAP S/4HANA Finance on Cloud: AI-Powered Deployment and Extensibility” - IJSAT-International Journal on Science and …16.1 2025 :1-14.

[11] Aragani, Venu Madhav and Maroju, Praveen Kumar and Mudunuri, Lakshmi Narasimha Raju, “Efficient Distributed Training through Gradient Compression with Sparsification and Quantization Techniques” (September 29, 2021). Available at SSRN: https://ssrn.com/abstract=5022841 or http://dx.doi.org/10.2139/ssrn.5022841

[12] Muniraju Hullurappa, Mohanarajesh Kommineni, “Integrating Blue-Green Infrastructure Into Urban Development: A Data-Driven Approach Using AI-Enhanced ETL Systems,” in Integrating Blue-Green Infrastructure Into Urban Development, IGI Global, USA, pp. 373-396, 2025.

[13] “Research highlights that organizations implementing both biometric authentication and tokenization have experienced a 92% reduction in fraud-related losses, while customer satisfaction scores have improved by 35% due to faster transaction processing times and reduced friction… biometric authentication systems have shown a 99.98% success [rate].”

[14] Ashima Bhatnagar Bhatia Padmaja Pulivarthi, (2024). Designing Empathetic Interfaces Enhancing User Experience Through Emotion. Humanizing Technology With Emotional Intelligence. 47-64. IGI Global.

[15] B. C. C. Marella, “Streamlining Big Data Processing with Serverless Architectures for Efficient Analysis,” FMDB Transactions on Sustainable Intelligent Networks., vol.1, no.4, pp. 242–251, 2024.

[16] Kirti Vasdev. (2025). “Churn Prediction in Telecommunications Using Geospatial and Machine Learning Techniques”. International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences, 13(1), 1–7. https://doi.org/10.5281/zenodo.14607920

[17] Praveen Kumar Maroju, "Optimizing Mortgage Loan Processing in Capital Markets: A Machine Learning Approach, " International Journal of Innovations in Scientific Engineering, 17(1), PP. 36-55 , April 2023.

[18] Panyaram, S., & Kotte, K. R. (2025). Leveraging AI and Data Analytics for Sustainable Robotic Process Automation (RPA) in Media: Driving Innovation in Green Field Business Process. In Driving Business Success Through Eco-Friendly Strategies (pp. 249-262). IGI Global Scientific Publishing.

[19] Mohanarajesh Kommineni. (2022/11/28). Investigating High-Performance Computing Techniques For Optimizing And Accelerating Ai Algorithms Using Quantum Computing And Specialized Hardware. International Journal Of Innovations In Scientific Engineering. 16. 66-80. (Ijise) 2022.

[20] “Research efforts are already underway to develop behavioral biometric modalities, such as gait, keystroke or touch dynamics, and voice, for user authentication… Behavioral biometrics can be combined with other authentication methods as an additional layer of authentication without disrupting device usage, improving the overall accuracy and device security.”

[21] Enhancement of Wind Turbine Technologies through Innovations in Power Electronics, Sree Lakshmi Vineetha Bitragunta, IJIRMPS2104231841, Volume 9 Issue 4 2021, PP-1-11.

[22] Pulivarthy, P. Enhancing Database Query Efficiency: AI-Driven NLP Integration in Oracle. Trans. Latest Trends Artif. Intell. 2023, 4, 4.

[23] V. M. Aragani and P. K. Maroju, "Future of blue-green cities emerging trends and innovations in iCloud infrastructure," in Advances in Public Policy and Administration, pp. 223–244, IGI Global, USA, 2024.

[24] Puvvada, Ravi Kiran. "Industry-Specific Applications of SAP S/4HANA Finance: A Comprehensive Review." International Journal of Information Technology and Management Information Systems(IJITMIS) 16.2 (2025): 770-782.

[25] Anumolu, V. R., & Marella, B. C. C. (2025). Maximizing ROI: The Intersection of Productivity, Generative AI, and Social Equity. In Advancing Social Equity Through Accessible Green Innovation (pp. 373-386). IGI Global Scientific Publishing.

[26] Gopichand Vemulapalli, Padmaja Pulivarthy, “Integrating Green Infrastructure With AI-Driven Dynamic Workload Optimization: Focus on Network and Chip Design,” in Integrating Blue-Green Infrastructure Into Urban Development, IGI Global, USA, pp. 397-422, 2025.

[27] “The proposed system integrates multi-factor authentication (MFA), biometric verification, and cryptographic security measures to enhance user authentication and prevent unauthorized access… By leveraging AI driven anomaly detection and blockchain based security, the system offers a robust framework against cyber threats, phishing attacks, and fraudulent transactions.”

[28] Venu Madhav Aragani, 2025, “Optimizing the Performance of Generative Artificial Intelligence, Recent Approaches to Engineering Large Language Models”, IEEE 3rd International Conference On Advances In Computing, Communication and Materials.

[29] Mr. G. Rajassekaran Padmaja Pulivarthy,Mr. Mohanarajesh Kommineni,Mr. Venu Madhav Aragani, (2025), Real Time Data Pipeline Engineering for Scalable Insights, IGI Global.

[30] DEEP LEARNING-BASED ANIMAL INTRUSION DETECTION AND WARNING SYSTEM FOR RAILROAD TRACKS, Sree Lakshmi Vineetha Bitragunta, International Journal of Core Engineering & Management, Volume-6, Issue-11, 2021, PP-292-301.

[31] Palakurti, A., & Kodi, D. (2025). “Building intelligent systems with Python: An AI and ML journey for social good”. In Advancing social equity through accessible green innovation (pp. 1–16). IGI Global.

[32] Pugazhenthi, V. J., Pandy, G., Jeyarajan, B., & Murugan, A. (2025, March). AI-Driven Voice Inputs for Speech Engine Testing in Conversational Systems. In SoutheastCon 2025 (pp. 700-706). IEEE.

[33] S. Panyaram, "Digital Twins & IoT: A New Era for Predictive Maintenance in Manufacturing," International Journal of Innovations in Electronic & Electrical Engineering, vol. 10, no. 1, pp. 1-9, 2024.

[34] Kirti Vasdev. (2022). “THE INTEGRATION OF GIS WITH CLOUD COMPUTING FOR SCALABLE GEOSPATIAL SOLUTIONS”. International Journal of Core Engineering & Management, 6(10, 2020), 143–147. https://doi.org/10.5281/zenodo.15193912

[35] Maroju, P. K. (2024). Advancing synergy of computing and artificial intelligence with innovations challenges and future prospects. FMDB Transactions on Sustainable Intelligent Networks, 1(1), 1-14.

[36] Vegineni, Gopi Chand, and Bhagath Chandra Chowdari Marella. "Integrating AI-Powered Dashboards in State Government Programs for Real-Time Decision Support." AI-Enabled Sustainable Innovations in Education and Business, edited by Ali Sorayyaei Azar, et al., IGI Global, 2025, pp. 251-276. https://doi.org/10.4018/979-8-3373-3952-8.ch011

[37] Pulivarthy, P. (2024). Gen AI Impact on the Database Industry Innovations. International Journal of Advances in Engineering Research (IJAER), 28(III), 1–10.

[38] Swathi Chundru, Lakshmi Narasimha Raju Mudunuri, “Developing Sustainable Data Retention Policies: A Machine Learning Approach to Intelligent Data Lifecycle Management,” in Driving Business Success Through EcoFriendly Strategies, IGI Global, USA, pp. 93-114, 2025.

[39] Optimized Technique for Maximizing Efficiency in GW-Scale EHVAC Offshore Wind Farm Connections through Voltage and Reactive Power Control, Sree Lakshmi Vineetha Bitragunta1 , Gokul Gadde2, IJIRMPS2106231842, Volume 9 Issue 6,2021, PP-1-12.

[40] Kotte, K. R., & Panyaram, S. (2025). Supply Chain 4.0: Advancing Sustainable Business. Driving Business Success Through Eco-Friendly Strategies, 303.

[41] Sandeep Sasidharakarnavar. “Enhancing HR System Agility through Middleware Architecture”. IJAIBDCMS [International JournalofAI,BigData,ComputationalandManagement Studies]. 2025 Mar. 14 [cited 2025 Jun. 4]; 6(1):PP. 89-97.

[42] Mohanarajesh Kommineni. Revanth Parvathi. (2013) Risk Analysis for Exploring the Opportunities in Cloud Outsourcing.

[43] C. C. Marella and A. Palakurti, “Harnessing Python for AI and machine learning: Techniques, tools, and green solutions,” In Advances in Environmental Engineering and Green Technologies, IGI Global, 2025, pp. 237–250

[44] Venu Madhav Aragani, Arunkumar Thirunagalingam, “Leveraging Advanced Analytics for Sustainable Success: The Green Data Revolution,” in Driving Business Success Through Eco-Friendly Strategies, IGI Global, USA, pp. 229- 248, 2025.

[45] Maroju, P.K.; Bhattacharya, P. Understanding Emotional Intelligence: The Heart of Human-Centered Technology. In Humanizing Technology with Emotional Intelligence; IGI Global Scientific Publishing: Hershey, PA, USA, 2025; pp. 1–18.

[46] Kodi, D. (2024). “Automating Software Engineering Workflows: Integrating Scripting and Coding in the Development Lifecycle “. Journal of Computational Analysis and Applications (JoCAAA), 33(4), 635–652.

[47] Khan, S., Noor, S., Javed, T. et al. “XGBoost-enhanced ensemble model using discriminative hybrid features for the prediction of sumoylation sites”. BioData Mining 18, 12 (2025). https://doi.org/10.1186/s13040-024-00415-8.

[48] Arpit Garg, “Behavioral Biometrics for IoT Security: A Machine Learning Framework for Smart Homes”, JRTCSE, vol. 10, no. 2, pp. 71–92, Oct. 2022, Accessed: Jul. 23, 2025. [Online]. Available: https://jrtcse.com/index.php/home/article/view/JRTCSE.2022.2.7

[49] Kovvuri, V. K. R. (2024). AI in Banking: Transforming Customer Experience and Operational Efficiency. International Journal for Multidisciplinary Research.[Online]. Available: https://www. ijfmr. com/papers/2024/6/31679. pdf.

Published

2025-05-18

How to Cite

1.
Riyana S. Enhancing Security in Digital Wallets Using Multi-Factor Authentication and Behavioral Biometrics. IJETCSIT [Internet]. 2025 May 18 [cited 2025 Sep. 13];:559-70. Available from: https://ijetcsit.org/index.php/ijetcsit/article/view/302

Similar Articles

1-10 of 190

You may also start an advanced similarity search for this article.