## 1 Introduction
To improve it for template protection, some researchers have extensively studied applying (1) cancellation with periodic transformation, (2) multimodal with more than two biometrics such as fingerprints, hand veins, face, palm veins, and so on, (3) lattice masks for providing several requirements (e.g., diversity and revocability) without the error correcting code, (4) smart card environments considering automatic fingerprint alignment, verification accuracy, template size, and (5) chaotic system-based multimodal considering the forgery, a significant difference of intra-class, and the security of unimodal biometric leakage [26; 27; 28; 29; 30; 31; 32]. Others have used it to share secret information or a secret key with conventional cryptography. Originally [PERSON] and his colleagues also introduced their scheme focusing on secret sharing or key distribution [13]. Many modified fuzzy vault schemes that use various biometric features (e.g., face, iris, or signature) have since been proposed based on this preliminary version and have tried various strategies to improve their performance [5; 33; 34; 35; 36; 37]. More recently, there have been attempts at applying a biometric cryptography scheme to physical unclonable function (PUF) [38], Body Area Networks (BAN) [2; 39; 40; 41; 42; 43], Electrocardiogram (ECG) [44], or wireless networks for symmetric key distribution through the transformation of fuzzy vault schemes. With each application, researchers have sought to improve the security, efficiency, or practicality of the fuzzy vault scheme; however, several problems still need to be solved [45; 46]. There is a drop-off in recognition rates when the number of chaff points increases, the runtime of higher order polynomial reconstruction is unrealistic for real-world applications, and the scheme remains vulnerable to a correlation attack [47; 48; 49]. In this paper, to solve these problems, we focus on the improved fuzzy vault for key or secret sharing. Significantly, our enhanced fuzzy vault scheme paves the way for the practical implementation of a secure, real-time authentication process, safeguarding the anonymity of drone operators for unmanned aerial vehicles (UAVs) you can trust. In the context of drone operation, where secure control and data privacy are paramount, our proposed system can authenticate operators securely and swiftly while maintaining their anonymity. This proposed implementation acknowledges the importance of ensuring security without sacrificing operator convenience and privacy. The anonymous operator authentication enabled by our enhanced fuzzy vault scheme demonstrates the potential of biometric cryptography in the increasingly prominent field of drone technology. The organization of this paper is as follows: Section 2 introduces the fuzzy vault scheme for binding biometric templates and sharing secret keys, Section 3 describes a genuine point generation scheme based on confidence interval analysis and uses it to improve the practicality of the fuzzy vault scheme, and Section 4 presents the analyzed result of it and compares the differences from the existing quantum modular adder. Finally, Section 5 presents conclusions.