Establishing the Validity of Md5 and Sha-1 Hashing in Digital Forensic Practice in Light of Recent Research Demonstrating Cryptographic Weaknesses in These Algorithms

Schmitt, Veronica; Jordaan, Jason

doi:10.5120/11723-7433

Cited by 7 publications

(1 citation statement)

References 5 publications

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“…The Bio-Cryptographic [32] [33] had been introduced for two purposes (i) to generate a strong cryptographic key from the biometric features and (ii) to protect the biometric features using strong cryptographic keys. Jain et al [34] had classified the BioCryptosystems into Key Generation and Key Binding where in Key Generation, the biometric key is directly generated from the biometric data [35] while in Key Binding, the biometric template and the secret key are tied up within a cryptographic framework and makes the system impossible to decode the biometric template or the key without any prior knowledge of biometric data [36]. The keys used for encryption and decryption cryptography can be further classified into two types: (i) Symmetric key also known as secret key or private key cryptography where both sender and receiver uses the same key for encryption and decryption and (ii) the Asymmetric key or public key uses one public key and another one private key.…”

Section: Biometric-cryptographymentioning

confidence: 99%

A Novel Cancelable FaceHashing Technique Based on Non-Invertible Transformation With Encryption and Decryption Template

et al. 2020

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A novel cancelable FaceHashing technique based on non-invertible transformation with encryption and decryption template has been proposed in this paper. The proposed system has four components: face preprocessing, feature extraction, cancelable feature extraction followed by the classification, and encryption/decryption of cancelable face feature templates. During face preprocessing, the facial region of interest has been extracted out to speed the process for evaluating discriminant features. In feature extraction, some optimization techniques such as Sparse Representation Coding, Coordinate descent, and Block coordinates descent have been employed on facial descriptors to obtain the best representative of those descriptors. The representative descriptors are further arranged in a spatial pyramid matching structure to extract more discriminant and distinctive feature vectors. To preserve them, the existing BioHashing technique has been modified and extended to some higher levels of security attacks and the modified BioHashing technique computes a cancelable feature vector by the combined effect of the facial feature vector and the assigned token correspond to each user. The elements of computed cancelable feature vector are in a numeric form that has been employed to perform both verifications as well as identification task in online while the original facial feature vectors are kept offline either in hard drive or disc. Then, to enhance more security levels and also to preserve the cancelable face features, an RSA based encryptiondecryption algorithm has been introduced. The proposed system has been tested using four benchmark face databases: CASIA-FACE-v5, IITK, CVL, and FERET, and performance are obtained as correct recognition rate and equal error rate. The performance are compared to the state-of-the-art methods for the superiority of the proposed feature extraction technique and individual performance analysis has been performed at all the security levels of the proposed Cancelable FaceHashing Technique. These comparisons show the superiority of the proposed system.

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Section: Biometric-cryptographymentioning

confidence: 99%