VLDB 2026 Research / reviewers in the wild / expert
Mulagala Sandhya
dblp:164/9139
· DBLP profile ↗
5ranked-venue papers
3as first author
3since 2021 · last 2025
0000-0003-2149-8584ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-authorSecurity and privacy · 2 · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Enhancing fingerprint template security using elliptic curve cryptography and fuzzy vault encoding
Praphul Kumar Maurya, Mulagala Sandhya, I. Hhntv Prasad, Nallaparaju V. Suryanarayanaraju |
J. Inf. Secur. Appl. | 2 |
| 2023 | Multi-instance cancelable iris authentication system using triplet loss for deep learning models
Mulagala Sandhya, Mahesh Kumar Morampudi, Indragante Pruthweraaj, Pranay Sai Garepally |
Vis. Comput. | 1 |
| 2022 | Securing multimodal biometric template using local random projection and homomorphic encryption
Dilip Kumar Vallabhadas, Mulagala Sandhya |
J. Inf. Secur. Appl. | 2 |
| 2018 | Multi-algorithmic cancelable fingerprint template generation based on weighted sum rule and T-operators
Mulagala Sandhya, Munaga V. N. K. Prasad |
Pattern Anal. Appl. | 1 |
| 2017 | Cancelable Fingerprint Cryptosystem Using Multiple Spiral Curves and Fuzzy Commitment SchemeabstractThe increased use of biometric-based authentication systems in a variety of applications has made biometric template protection an important issue. Unlike conventional systems, biometric cannot be revoked or changed. This made template protection a critical issue to be considered in the recent years. This paper proposes a cancelable fingerprint cryptosystem using multiple spiral curves and fuzzy commitment scheme. The method is built by combining cancelable biometrics and biometric cryptosystems. First, we compute transformed minutiae features using multiple spiral curves. Further, these transformed features are encrypted using fuzzy commitment scheme. Hence, a secure template is obtained. Experimental results and analysis prove the credibility of proposed method with recently presented methods of fingerprint template protection. Mulagala Sandhya, Munaga V. N. K. Prasad |
Int. J. Pattern Recognit. Artif. Intell. | 1 |