Cryptography based Internet Security ATM System using Fingerprint for securing PIN

Today, ATMs (automated teller machines) are used in a variety of ways, including: you can withdraw cash, transfer cash, check your balance, get an account summary, and more. The main component here is security, to maintain the security we prefer cryptography and biometrics. Cryptography is a state- of-the-art technique for increasing security. Using cryptography and biometrics together creates a bio cryptographic system. Since the private key is an important component of encryption, here one is the main task to secure the private [1] key. To overcome this issue, we use a biometric fingerprint image. However, biometrics cannot protect anyone’s fingerprint template because of the many suspected attacks. Therefore, we use a fuzzy vault system that combines cryptography [2] and biometrics [4] to ensure that only authorized users can use their passwords and PINs with the legal data. Keywords: Biometrics, Cryptography, Fuzzy vault system, IP security, Java Applets.

A fuzzy vault development based on iris images

Biometric systems gather information from the person's biometric attributes, used extensively to authorize the individuals. Due to the obvious convenience of using specific individual traits such as face, fingerprints, palm veins, and irises, biometric authentication is becoming more common. In particular, Iris systems are in high demand for high-assurance applications, because they contain a broad feature set and remain stable. Authentication methods based on iris biometrics are now commonly used in a variety of fields. This is due to the fact that iris biometric authentication is both safer and more comfortable than conventional passwords. Template Security is a major concern in biometric systems. The template security mechanism ensures reusable, permanent, and un-linkable models. The Fuzzy Vault strategy is one of the most popular security schemes for Template protection. Fuzzy vault has demonstrated to be an effective protection method but lacks revocability and security attacks. This article introduced an improved fuzzy vault system. The improved fuzzy vault system was introduced, which uses more than one key to protect biometric data. Different keys make the search space more detailed. The additional key was used to encrypt vault data, which stopped the intruder from accessing the information on the person's biometry. The system was tested using CASIA.v1 and IITD.v1 datasets, and findings showed that the system ensures the protection and authentication of the iris templates without compromising performance. The proposed modification gave a 0.0 % False Accepted Rate (FAR) for both the dataset and False Rejected Rate (FRR), 0.14 % for CASIA v1 and 0.12 % for ITTD v1 False Rejected rate

Secure Online Examination with Biometric Authentication and Blockchain-Based Framework

E-learning has been carried out all over the world and then online examinations have become an important means to check learning effect during the outbreak of COVID-19. Participant authenticity, data integrity, and access control are the assurance to online examination. The existing online examination schemes cannot provide the protection of biometric features and fine-grained access control. Particularly, they did not discuss how to resolve some disputes among students, teachers, and a platform in a fair and reasonable way. We propose a novel biometric authentication and blockchain-based online examination scheme. The examination data are encrypted to store in a distributed system, which can be obtained only if the user satisfies decryption policy. And the pieces of evidence are recorded in a blockchain network which is jointly established by some credible institutions. Unlike other examination authentication systems, face templates in our scheme are protected using a fuzzy vault and a cryptographic method. Furthermore, educational administrative department can determine who the real initiator of malicious behavior is when a dispute arises using a dispute determination protocol. Analysis shows that no central authority is required in our scheme; the collusion of multiple users cannot obtain more data; even if the authorities compromise, biometric features of each user will not be leaked. Therefore, in terms of privacy-preserving biometric templates, fine-grained access, and dispute resolution, it is superior to the existing schemes.

Secure Chaff-less Fuzzy Vault for Face Identification Systems

Biometric cryptosystems such as fuzzy vaults represent one of the most popular approaches for secret and biometric template protection. However, they are solely designed for biometric verification, where the user is required to input both identity credentials and biometrics. Several practical questions related to the implementation of biometric cryptosystems remain open, especially in regard to biometric template protection. In this article, we propose a face cryptosystem for identification (FCI) in which only biometric input is needed. Our FCI is composed of a one-to-N search subsystem for template protection and a one-to-one match chaff-less fuzzy vault (CFV) subsystem for secret protection. The first subsystem stores N facial features, which are protected by index-of-maximum (IoM) hashing, enhanced by a fusion module for search accuracy. When a face image of the user is presented, the subsystem returns the top k matching scores and activates the corresponding vaults in the CFV subsystem. Then, one-to-one matching is applied to the k vaults based on the probe face, and the identifier or secret associated with the user is retrieved from the correct matched vault. We demonstrate that coupling between the IoM hashing and the CFV resolves several practical issues related to fuzzy vault schemes. The FCI system is evaluated on three large-scale public unconstrained face datasets (LFW, VGG2, and IJB-C) in terms of its accuracy, computation cost, template protection criteria, and security.

A Enhanced Security Alignment-Free Fuzzy Vault-Based Pattern Cryptosystem Using Pair-Polar Details Arrangements

Numerous methods are executed to perform unique mark acknowledgment approach, and every procedure dependent on explicit standards. The point of this work is to locate an effective finger impression acknowledgment procedure. This venture attempts to offer a straightforward superior way to deal with perform finger impression acknowledgment. This methodology dependent on two fundamental stages; the first is the genuine information assortment of human unique mark tests and the subsequent stage is focused on plan and usage of elite finger impression acknowledgment approach. The executed methodology focused on the component extraction part in which numerous degrees of two dimensional discrete cosine change (2D-DCT) are utilized to create superior element. This methodology is executed by means of blending the highlights of both right finger thumb and left finger thumb. The outcomes demonstrate that a decent precision of acknowledgment is gotten by this methodology.