Work place: Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Knowledge Corridor, Gandhinagar, Gujarat 382007
E-mail:
Website: https://orcid.org/0000-0003-2786-1145
Research Interests:
Biography
Nandini Modi, an IEEE member, currently serves as an Assistant Professor in the Computer Science and Engineering department at Pandit Deendayal Energy University, Gandhinagar. She holds a PhD in Eye gaze tracking during Human computer interactive applications. She is working in the field of computer vision, cognitive science and its applications. Areas of interests include Human computer interaction, Eye gaze tracking, Sentiment analysis, Machine learning, Cognitive computing, smart healthcare solutions. She has contributed to various international conferences and holds intellectual property rights for several innovations. She is also a reviewer for multiple prestigious journals and a member of several professional organizations.
By Mukesh Kumar Vivek Bhardwaj Karan Bajaj Nandini Modi Ahmed Qtaishat
DOI: https://doi.org/10.5815/ijieeb.2025.03.03, Pub. Date: 8 Jun. 2025
This paper presents the implementation and evaluation of a Multi-key Multi-modalities Biometric Encryption System designed for business enterprises, leveraging cloud storage for secure and scalable data management. The system integrates multiple biometric modalities fingerprint, iris scan, and face recognition to enhance data security through advanced multi-key encryption techniques, utilizing algorithms such as Advanced Encryption Standard (AES) and Rivest-Shamir-Adleman (RSA). The encrypted biometric data is securely stored in the cloud, providing enterprises with efficient storage solutions. The system's performance was evaluated across several parameters including encryption/decryption time, biometric match accuracy, data transfer speeds, energy consumption, cost, and user satisfaction. The results demonstrate that multi-modal systems offer superior accuracy and security compared to single-modality systems, reducing error rates and enhancing reliability. However, multi-modal authentication incurs higher costs, energy consumption, and slightly longer processing times. Despite these trade-offs, the system achieved high user satisfaction, particularly in high-security environments where data protection is a priority. The findings indicate that the proposed system is a viable solution for businesses seeking a secure, scalable, and efficient method of protecting sensitive data.
[...] Read more.Subscribe to receive issue release notifications and newsletters from MECS Press journals