Biometric key generation techniques are used to reliably generate cryptographic material from biometric signals. Existing constructions require users to perform a particular activity (e.g., type or say a password, or provide a handwritten signature), and are therefore not suitable for generating keys continuously. In this paper we present a new technique for biometric key generation from free-text keystroke dynamics. This is the first technique suitable for continuous key generation. Our approach is based on a scaled parity code for key generation (and subsequent key reconstruction), and can be augmented with the use of population data to improve security and reduce key reconstruction error. In particular, we rely on linear discriminant analysis (LDA) to obtain a better representation of discriminable biometric signals. To update the LDA matrix without disclosing user's biometric information, we design a provably secure privacy-preserving protocol (PP-LDA) based on homomorphic encryption. Our biometric key generation with PP-LDA was evaluated on a dataset of 486 users. We report equal error rate around 5 when using LDA, and below 7 without LDA.
Monrose al @cite_12 evaluate the performance of BKG based on spoken password using data from 50 users. They report a false-negative rate of 4 Handwritten signature is another behavioral modality, where biometric key generation has been studied. Multiple papers, for example by Freire al @cite_10 , Feng al @cite_13 and more recently Scheuermann al @cite_18 evaluate the performance. The dataset sizes for the first three papers are 330, 25 and 144 users; the last paper does not include the number of users. The false accept false reject rates presented are 57 Physical biometrics have also been used for biometric key generation, evaluated on fingerprints by Clancy @cite_14 al, Uludag al @cite_11 , Sy and Krishnan @cite_15 and others. BKG on iris was studied by Rathgeb and Uhl @cite_2 , @cite_16 and Wu al @cite_20 , and on face images by Chen al @cite_17 .
@cite_18 @cite_14 @cite_10 @cite_20 @cite_17 @cite_2 @cite_15 @cite_16 @cite_13 @cite_12 @cite_11
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In this paper, the fundamental insecurities hampering a scalable, wide-spread deployment of biometric authentication are examined, and a cryptosystem capable of using fingerprint data as its key is presented. For our application, we focus on situations where a private key stored on a smartcard is used for authentication in a networked environment, and we assume an attacker can launch o -line attacks against a stolen card.Juels and Sudan's fuzzy vault is used as a starting point for building and analyzing a secure authentication scheme using fingerprints and smartcards called a figerprint vault. Fingerprint minutiae coordinates mi are encoded as elements in a nite eld F and the secret key is encoded in a polynomial f(x) over F[x]. The polynomial is evaluated at the minutiae locations, and the pairs (mi, f(mi)) are stored along with random (ci, di) cha points such that di ≠ f(ci). Given a matching fingerprint, a valid user can seperate out enough true points from the cha points to reconstruct f(x), and hence the original secret key.The parameters of the vault are selected such that the attacker's vault unlocking complexity is maximized, subject to zero unlocking complexity with a matching fingerprint and a reasonable amount of error. For a feature location measurement variance of 9 pixels, the optimal vault is 269 times more difficult to unlock for an attacker compared to a user posessing a matching fingerprint, along with approximately a 30 chance of unlocking failure. Based on recent works showing the feasibility of key generation using biometrics, we study the application of handwritten signature to cryptography. Our signature-based key generation scheme implements the cryptographic construction named fuzzy vault. The use of distinctive signature features suited for the fuzzy vault is discussed and evaluated. Experimental results are reported, including error rates to unlock the secret data by using both random and skilled forgeries from the MCYT database. Biometric cryptography is a technique using biometric features to encrypt data, which can improve the security of the encrypted data and overcome the shortcomings of the traditional cryptography. This paper proposes a novel biometric cryptosystem based on the most accurate biometric feature - iris. In encryption phase, a quantified 256-dimension textural feature vector is firstly extracted from the preprocessed iris image using a set of 2-D Gabor filters. At the same time, an error-correct-code (ECC) is generated using Reed-Solomon algorithm. Then the feature vector is translated to a cipher key using Hash function. Some general encryption algorithms use this cipher key to encrypt the secret information. In decryption phase, a feature vector extracted from the input iris is firstly corrected using the ECC. Then it is translated to the cipher key using the same Hash function. Finally, the corresponding general decryption algorithms use the key to decrypt the information. Experimental results demonstrate the feasibility of the proposed system. Existing asymmetric encryption algorithms require the storage of the secret private key. Stored keys are often protected by poorly selected user passwords that can either be guessed or obtained through brute force attacks. This is a weak link in the overall encryption system and can potentially compromise the integrity of sensitive data. Combining biometrics with cryptography is seen as a possible solution but any biometric cryptosystem must be able to overcome small variations present between different acquisitions of the same biometric in order to produce consistent keys. This paper discusses a new method which uses an entropy based feature extraction process coupled with Reed-Solomon error correcting codes that can generate deterministic bit-sequences from the output of an iterative one-way transform. The technique is evaluated using 3D face data and is shown to reliably produce keys of suitable length for 128-bit Advanced Encryption Standard (AES). In this work we present a new technique for generating cryptographic keys out of iris textures implementing a key-generation scheme. In contrast to existing approaches to iris-biometric cryptosystems the proposed scheme does not store any biometric data, neither in raw nor in encrypted form, providing high secrecy in terms of template protection. The proposed approach is tested on a widely used database revealing key generation rates above 95 . Cryptographic approach, on the other hand, ties data protection mathematically to the Key that is utilized to protect it. This allows a data owner to have complete control over one’s personal information without relying on, or relinquishing control to, a third party authority. The protection of personal sensitive information is also not tied to complex software and hardware systems that may need constant patches. In order to increase security in common key management systems, the majority of so-called Biometric Cryptosystems aim at coupling cryptographic systems with biometric recognition systems. As a result these systems produce cryptographic keys, dependent on biometric information, denoted Biometric Keys. In this work a generic approach to producing cryptographic keys out of biometric data is presented, by applying so-called Interval-Mapping techniques. The proposed scheme is adapted to iris, which has not yet been examined according to this technique, as well as on-line signatures to demonstrate that this approach is generic. Performance results show that the approach pays off. n recent years, public key infrastructure (PKI) has emerged as co‐existent with the increasing demand for digital security. A digital signature is created using existing public key cryptography technology. This technology will permit commercial transactions to be carried out across insecure networks without fear of tampering or forgery. The relative strength of digital signatures relies on the access control over the individual’s private key. The private key storage, which is usually password‐protected, has long been a weak link in the security chain. In this paper, we describe a novel and feasible system – BioPKI cryptosystem – that dynamically generates private keys from users’ on‐line handwritten signatures. The BioPKI cryptosystem eliminates the need of private key storage. The system is secure, reliable, convenient and non‐invasive. In addition, it ensures non‐repudiation to be addressed on the maker of the transaction instead of the computer where the transaction occurs. We propose a technique to reliably generate a cryptographic key from a user's voice while speaking a password. The key resists cryptanalysis even against an attacker who captures all system information related to generating or verifying the cryptographic key. Moreover, the technique is sufficiently robust to enable the user to reliably regenerate the key by uttering her password again. We describe an empirical evaluation of this technique using 250 utterances recorded from 50 users.