Securing cryptographic key with fuzzy vault based on a new chaff generation method

The fuzzy vault is an innovative way to share secret keys, combining traditional cryptography with biometrics and biometric template protection. This method forms the basis for the reliable operation of unmanned aerial vehicles (UAVs) through anonymizing drone operators and safely using their data and onboard information. However, due to the inherent instability of biometrics, traditional fuzzy vault schemes face challenges, such as reduced recognition rates with increased chaff points, impractical runtimes due to high-order polynomial reconstruction, and susceptibility to correlation attacks. This paper proposes an efficient fuzzy vault scheme to address these challenges. We generate two secret keys based on biometrics: the first key is produced from the operator’s unique features like the face and iris, using a confidence interval; the second key, used to construct a polynomial, is based on what the operator remembers. These dual-key fuzzy vaults enable the stable generation of genuine points during encoding, easy extraction during decoding, and effective operator authentication while maintaining anonymity. Our experimental results demonstrate improved security and secret acquisition accuracy using the AR face database. These results are achieved regardless of increased false vaults, enabling real-time polynomial reconstruction and resilience against correlation attacks. Importantly, our enhanced fuzzy vault scheme allows the application of this secure, real-time authentication process, safeguarding the anonymity of drone operators.

Based on the classical fuzzy vault and the Diffie-Hellman key exchange scheme, a key sharing fuzzy vault scheme is proposed. In this fuzzy vault scheme, the two users cooperatively build their shared fuzzy vault with a shared key hidden in it using their own biometric features, and they can respectively use their biometric features to unlock the fuzzy vault to get their shared key without running the risk of disclosure of their biometric features later. The security of our scheme is based on the security of the classical fuzzy vault scheme and and the discrete logarithm problem in a given finite group.

The fuzzy vault algorithm is mainly used for data privacy protection in fault-tolerant environments, It binds biometric features and secret data together safely to form a vault, which can realize "fuzzy" unlocking. in the real-life, fuzzy vault is mainly used in biometric authentication, image capture, recognition, etc. However, At present, most fuzzy vault schemes have the problems of high computational complexity and low communication efficiency. To solve the problems of high computational complexity and low communication efficiency in identity authentication, we based on the fuzzy vault scheme and construct a multi-secret sharing fuzzy vault scheme. which splits the big secret value into multiple sub-secret values and uses the RS code multi-secret sharing decoding method to improve the efficiency of biological identity authentication. Firstly, splits the big secret value into multiple sub-secret values. Then, We construct a multi-secret sharing scheme. our scheme supports the sharing of multi-secret information. Finally, we analyze the computational complexity and communication complexity of the scheme. The analysis shows that our scheme can reduce the computational complexity and communication complexity by an order of magnitude.

Biometric cryptosystem has emerged as a promising solution in information security. Fuzzy vault is a widely accepted scheme that binding biometric data and cryptography effectively. In vault encoding, random chaff points which are not on the polynomial are added to protect genuine points. In vault decoding, query biometric data is generated to retrieve the genuine points by measuring the distance between the registered data and query data. However, because of the within-class differences and randomness of chaff points, it is difficult to distinguish the genuine data from chaff data. This paper proposes a novel 3D fuzzy vault scheme that selects unused data from template feature vector and inserts it into the genuine points. In our scheme, every point in the vault has three dimensions, two of which could be used for distance measurement. The precision of the data matching is improved by the new inserted data and genuine points could be recognized more accurately. Experimental results based on HA-BJTU database show the better performances compared to traditional fuzzy vault.

Nowadays, the crypto-biometric schemes are commonly studied to deal with the key management problem existing in cryptographic systems. In the paper we consider a well-known fuzzy vault scheme working on non-standard biometric data associated with palm-oriented gestures. We discuss the usefulness of the touch-less palm tracking system focused on handling the biomechanical characteristics of one's hand to protect the cryptographic key or other secret data. As a behavioral template the fixed finger-based gesture is applied. In order to generate unordered sets for fuzzy vault we use the global approach where features are decoded from fingertip position and velocity. Both the raw and DCT-calculated time series are preprocessed to solve the instability and variability problem strictly related to behavioral character of the data. We provide the experimental results and discuss the security issues.

A combination of cryptographic and biometric systems, by performing specific binding technique on cryptographic key and biometric template, the fuzzy vault framework enhances the security level of current biometric cryptographic systems in terms of hiding secret key and protecting the template. Although the original scheme suggests the use of error-correction techniques (e.g. the Reed–Solomon code) to reconstruct the original polynomial, recent implementations do not share the same point of view. Instead, cyclic redundant code (CRC) is applied to identify the genuine polynomial from a set of candidates due to its simplicity. Within the scope of this study, the authors address a significant flaw of current CRC-based fuzzy vault schemes, which allows the potential of successful blend substitution attack. To overcome this problem, an integration of two novel modules into general fuzzy vault scheme, namely chaff point generator and verifier, is proposed. The new modules are designed to be integrated easily into the existing systems as well as simple to enhance. The proposed scheme can detect any modification in vault and, as a result, eliminate the blend substitution attack to improve general security. Moreover, the experimental results of this study with real-world datasets show an increase in genuine acceptance rates.

A novel key sharing fuzzy vault scheme is proposed based on the classic fuzzy vault and the Diffie-Hellman key exchange protocol. In this proposed scheme, two users cooperatively build their fuzzy vault for their shared key using their own biometrics. Either of the users can use their own biometrics to unlock the fuzzy vault with the help of the other to get their shared key without risk of disclosure of their biometrics. Thus, they can unlock the fuzzy vault cooperatively. The security of our scheme is based on the security of the classic fuzzy vault scheme, one-way hash function and the discrete logarithm problem in a given finite group.

Template security of biometric systems is a vital issue and needs critical focus. The importance lies in the fact that unlike passwords, stolen biometric templates cannot be revoked. Hence, the biometric templates cannot be stored in plain format and needs strong protection against any forgery. In this paper, we present a technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem. Here, initially the input images are pre-processed using various processes to make images fit for further processing. In our proposed method, the features are extracted from the processed hand and palm vein images by finding out unique common points. The chaff points are added to the already extracted points to obtain the combined feature vector. The secret key points which are generated based on the user key input (by using proposed method) are added to the combined feature vector to have the fuzzy vault. For decoding, the multi-modal biometric template from palm vein and hand vein image is constructed and is combined with the stored fuzzy vault to generate the final key. Finally, the experimentation is conducted using the palm vein and hand vein database. The evaluation metrics employed are FMR (False Match Ratio) and GMR (Genuine Match Ratio). From the metric values obtained for the proposed system, we can infer that the system has performed well. The results are also compared to our earlier technique and the results shows that the proposed technique has achieved better results having GAR of 94% without noise and 88% with noise.

Biometric systems accumulate information from biometric elements of an individual and used to exceptionally confirm the person with the physical and behavioral properties of the biometric characteristic. Biometrics and cryptography systems have been identified as the two main components of digital security system. Cryptography is combined with biometric to achieve high security. In this paper, fingerprint template protection is proposed which is based on fuzzy vault scheme. Initially, enrolled fingerprint images are preprocessed using some image processing techniques and preprocessed images are prealigned automatically using directed reference point. All the minutiae points are extracted and extracted minutiae features along with secret key are used to produce the fuzzy vault. Query features are given as an input with the stored template to recover the corresponding key. The proposed method is validated on FVC 2002 database. Simulation results prove that the proposed method can achieve high genuine acceptance rate with improved security.

Theft of a template is theft of identity. Fingerprint identification is used by forensic department in identifying criminals because of its uniqueness. Biometrics is the science of verifying and establishing the identity of an individual through physiological features or behavioral traits. Fingerprint identification is commonly employed in Forensic science to support criminal investigations and in biometric systems such as civilian and commercial identification devices. The best way to identify criminals is using fingerprint verification which cannot be replaced. So such fingerprint acquired from the criminal should be safely stored and protected from hackers for future references. This paper mainly deals with protecting the criminal's record (fingerprint template). Templates represent intrinsic information about a criminal. The criminal record (Fingerprint template) should be protected from creation of physical spoof and replacement by imposter's template to gain unauthorized access. Due to these reasons, fool-proof techniques are required for securely storing the criminal fingerprint records. Fuzzy vault is a cryptographic construct that is designed to work with biometric features represented as an unordered set like minutiae points. Template protection is done by transformation based approaches and biometric cryptosystems. During transformation template is stored in a transformed form so that the original biometric template cannot be easily recovered. Fingerprint from the criminal is first preprocessed and minutiae points are extracted. Preprocessing is very essential because the creation of fuzzy vault highly depends on the quality of the input fingerprint image. Then image is binarized followed by thinning and then region of interest (ROI) is calculated finally followed by removal of false minutiae points. The remaining useful minutiae points are used in fuzzy vault generation. A polynomial is evaluated from the secret key which is combined with minutiae points to produce a secure vault. Some dummy points called chaff points are also added to increase the security. The security of the fuzzy vault depends on the infeasibility of the polynomial reconstruction and the number of chaff points. In the proposed system an even more secured fuzzy vault is generated with combined features of fingerprint and palm print to enhance the security of the template stored.

We construct an automatic secure fingerprint verification system based on the fuzzy vault scheme to address a major security hole currently existing in most biometric authentication systems. The construction of the fuzzy vault during the enrollment phase is automated by aligning the most reliable reference points between different templates, based on which the converted features are used to form the lock set. The size of the fuzzy vault, the degree of the underlying polynomial, as well as the number of templates needed for reaching the reliable reference point are investigated. This results in a high unlocking complexity for attackers with an acceptable unlocking accuracy for legal users.

The fuzzy vault scheme has recently become popular approaches to biometric template protection. Since the original scheme has been designed to work with unordered biometric features, such a scheme cannot effectively utilize order information. We present in this paper a new fuzzy vault scheme that can effectively utilize the ordered characteristics of biometric features. In this scheme, we develop ordered fuzzy vault encoding and decoding processes in order to utilize the ordered information of the features. This prevents the feature components from cross matching and reduces false acceptance ratio (FAR). Furthermore, the original biometric features (or original template) are transformed into binary features (or secure template) by random transformation. The transformed secure template provides both diversity and revocability. This transform also prevents an adversary from obtaining the original biometric template from the secure template and therefore enhance the secure level of the scheme. Based on the proposed scheme, we design an online authentication application framework implemented using face images. We compare our scheme with two contemporary approaches to verify the effectiveness of this approach. Experimental results show that our scheme is able to achieve an improved performance with several desired properties of an online authentication system.

Multimodal biometric user authentication using improved decentralized fuzzy vault scheme based on Blockchain network

Template security of biometric systems is a vital issue and needs critical focus. The importance lies in the fact that unlike passwords, stolen biometric templates cannot be revoked. Hence, the biometric templates cannot be stored in plain format and needs strong protection against any forgery. In this paper, we present a technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem. Here, initially the input images are pre-processed using various processes to make images fit for further processing. In our proposed method, the features are extracted from the processed face and palm vein images by finding out unique common points. The chaff points are added to the already extracted points to obtain the combined feature vector. The secret key points which are generated based on the user key input (by using proposed method) are added to the combined feature vector to have the fuzzy vault. For decoding, the multi-modal biometric template from palm vein and face image is constructed and is combined with the stored fuzzy vault to generate the final key. Finally, the experimentation is conducted using the palm vein and face database available in the CASIA and JAFFE database. The evaluation metrics employed are FMR (False Match Ratio) and GMR (Genuine Match Ratio). From the metric values obtained for the proposed system, we can infer that the system has performed well.

As a consequence of the wide deployment of biometrics-based recognition systems, there are increasing concerns about the security of the sensitive information managed. Various techniques have been proposed in the literature for the biometric templates protection (BTP), having gained great popularity the crypto-biometric systems. In the present paper we propose the implementation of a Fuzzy Vault (FV) scheme based on fixed-length templates with application to dynamic signature verification (DSV), where only 15 global features of the signature are considered to form the templates. The performance of the proposed system is evaluated using three databases: a proprietary collection of signatures, and the publicly available databases MCYT and BioSecure. The experimental results show very similar verification performance compared to an equivalent unprotected system.