Optical Ciphering Scheme for Cancellable Speaker Identification System

A novel cancellable biometric recognition system based on Rubik’s cube technique for cyber-security applications

In this paper, we propose a method for the numerical simulation of optical double random phase encoding (DRPE). This method is based on a discrete model of the DRPE system that retains the properties of its optical counterpart and takes into account the capacity of DRPE to spread a signal’s energy in both the space and the spatial frequency domains. Discrete versions of two narrowband lossless diffusers are created to simulate their analogue optical counterparts and their bandwidths control how much the energy of the input signal is spread in both the space and spatial frequency domains as it passes through the system. The limiting case, when complete aliasing (maximum overlap) takes place, is also discussed in relation to our method. In this case, we show our method reduces to a purely numerical encryption procedure which can, nonetheless, be decrypted perfectly. Simulation results are presented to demonstrate the feasibility of the proposed technique.

Cancelable biometric techniques play a vital role in the privacy and security of remote surveillance systems to keep the genuine users’ confidential data safe and away from intruders. This research presents an efficient cancelable biometric framework by exploiting an irreversible hybrid encryption technique that incorporates Deoxyribonucleic, Ribonucleic acid sequences (DNA and RNA), and the evolutionary optimization technique of the Genetic Algorithm (GA). So, these techniques are employed to create completely deformed templates from their original ones. Thus, our main contribution is offering a novel biometric security framework that achieves unique randomness characteristics using RNA and DNA sequences and the evolutionary GA-based encryption scheme. The proposed framework produces an entirely unrecognized biometric template by ciphering the main discriminative features of the biometric traits of the authorized clients. The proposed algorithm is first initialized by creating several encrypted biometric images of the original users by employing the logistic map function. Secondly, the initialized encrypted images are transformed into one vector of a binary array. Then, they are converted to their corresponding introns, exons, and consequently, their relevant codons are stored in the cloud database. Thirdly, these relevant codons are replaced by new ones after generating encrypted RNA lists. The utilized encryption key is extracted from the original biometric image after utilizing excessive permutations between its pixels. Then, the GA-based optimization technique is applied to select the most convenient biometric features. Finally, after employing the GA-based cross-over and mutation operations, the chosen features are used to generate the cancelable biometric traits. To validate the security efficacy of the proposed framework, different six biometric databases are used, which are Olivetti Research Laboratory (ORL) Faces (gray), CASIA v.5 Faces (color), UPOL Iris (gray), Indian Institute of Technology Delhi (IIT Delhi) Ear (color and gray), Fingerprint, and CASIA Palmprint (color and gray). The security performance of the proposed framework is compared to those of recent studies in this field, such as OSH (Optical Scanning Holography) and DRPE (Double Random Phase Encoding). The simulation results prove the superior performance of the proposed framework in terms of all tested evaluation metrics. The proposed framework provides high AROC (Area under the Receiver Operating Characteristic) that reaches 0.9990, low FAR (False Acceptance Rate) of 0.0015, more uniform histograms, high correlation values for genuine users, and complete hidden of biometric features. In addition, from a security perspective, the proposed framework accomplishes good entropy, UACI (unified average changing intensity), and NPCR (number of pixels change rate) values that reach 7.9960, 33.55%, and 99.65%, respectively.

A security-enhanced multiple-image encryption method is proposed based on quick response (QR) codes and modified double random phase encoding (DRPE) in the fractional Fourier transform (FrFT) domain in this paper, where each plaintext is first converted into QR code, and then each QR code is employed to generate the corresponding binary key for decryption with the help of random binary plaintext (RBP). Subsequently, the used RBP is encrypted into noise-like ciphertext by using the modified DRPE in the FrFT domain. In the modified DRPE method, the first random phase mask is activated by the initial FrFT with chaotic phase, and the wavelength of light and the fractional orders as well as the focal lengths of lenses are all used as digital keys to expand the key space. Moreover, the sensitivities of these digital keys are extremely high because the digital keys are closely mapped with the initial values of the chaotic system in the encryption process, which contributes to an extremely high security of the multiple-image encryption method. Furthermore, the high feasibility and strong robustness of the proposed security-enhanced multiple-image encryption method are also demonstrated by using computational simulations.

Most of the existing selective encryption schemes are based on image processing and cannot be realized by optical structures, so their practicality is limited. Combining the optical design, a local hybrid optical encryption system based on double random phase encoding is proposed. The system proposed in this paper possesses a common aperture and dual optical path structure, which is widely used in optical design and can effectively improve the practicality of optical encryption system. First, important information and non-important information in the original image are separated by a selective beam splitter. Then light waves carrying important information enter into the 4<i>f</i> system for encryption, and light waves carrying non-important information enter into the diffraction system for encryption. Finally, part of the diffraction system ciphertext is replaced with 4<i>f</i> system ciphertext to obtain the final encrypted image. Decryption is the reverse process of encryption. First, the 4<i>f</i> system ciphertext is cut out from the final ciphertext. Then the 4<i>f</i> system ciphertext is used to restore the information replaced in the diffraction system ciphertext, thereby obtaining the complete diffraction system ciphertext. Finally, the two ciphertexts go through the reverse process of their respective systems to complete the decryption. By comparing the statistical characteristics and mean square error of the original image and the encrypted image, the effectiveness of the proposed system's encryption process is proved. By analyzing the peak signal-to-noise ratio of the original image and the decrypted image, the effectiveness of the proposed system's decryption process is proved. The sensitivity of each key of the system is analyzed to prove the security of the system. Especially the system is highly sensitive to selective encryption key, which proves the effectiveness and security of the proposed system for selective encryption. Through simulation, it is verified that the proposed system is very resistant to diffraction attacks. Even if he can obtain all the diffraction keys, the attacker still cannot obtain the selectively encrypted information. Finally, through simulation, it is verified that the proposed system has good noise resistance and crop resistance, and high robustness as well. The proposed system can realize the selective encryption through optical structure, which is safe, effective and highly robust, and thus improving the practicality of selective optical encryption system.

Despite their usability advantages over traditional authentication systems, biometrics-based authentication systems suffer from inherent privacy violation and non-revocability issues. In order to address these issues, the concept of cancelable biometrics was introduced as a means of generating multiple, revocable, and noninvertible identities from true biometric templates. Apart from BioHashing, which is a two-factor cancelable biometrics technique based on mixing a set of tokenized user-specific random numbers with biometric features, cancelable biometrics techniques usually cannot preserve the recognition accuracy achieved using the unprotected biometric systems. However, as the employed token can be lost, shared, or stolen, BioHashing suffers from the same issues associated with token-based authentication systems. In this paper, a reliable tokenless cancelable biometrics scheme, referred to as BioEncoding, for protecting IrisCodes is presented. Unlike BioHashing, BioEncoding can be used as a one-factor authentication scheme that relies only on sole IrisCodes. A unique noninvertible compact bit-string, referred to as BioCode, is randomly derived from a true IrisCode. Rather than the true IrisCode, the derived BioCode can be used efficiently to verify the user identity without degrading the recognition accuracy obtained using original IrisCodes. Additionally, BioEncoding satisfies all the requirements of the cancelable biometrics construct. The performance of BioEncoding is compared with the performance of BioHashing in the stolen-token scenario and the experimental results show the superiority of the proposed method over BioHashing-based techniques.

Cancelable biometrics has been proposed for canceling and re-issuing biometric templates and for protecting privacy in biometrics systems. Recently, new cancelable biometric approaches are proposed based on BioHashing, which are random transformed feature-based cancelable biometrics. In this paper, we consider the accuracy of one of the cancelable biometrics based on BioHashing and face. Through this analysis, as an illustration, we would like to raise an issue to be considered in cancelable biometrics: accuracy may be traded for biometrics being cancelable.

The present work is devoted to research the peculiarities of an authentication system of the technical devices with the use of an optical asymmetric holographic encryption on the basis of the Double Random Phase Encoding (DRPE). The series of the numerical experiments was performed to implement the encryption and the decryption of the initial image. The angular spectrum approach was used as a tool for the simulation of the propagation of the light in the free space forward and backward along the whole optical scheme of the DRPE. In the present work the particularities of the authentication system based on an asymmetric approach of the holographic encryption method DRPE were studied.

Biometrics plays a vital role in security through authentication and verification. Securing the biometric template is the current challenge field of research. As intruders attack the biometric system which affects the applications which are being used for human authentication. To name a few border security, access control surveillance and so on. Vulnerabilities too affect the protected templates at the time of biometric verification process. Biometric templates can be protected by using the techniques like transformation or cancelable biometrics, biometrics cryptosystem, and hybridization. Most of the vulnerabilities or attacks are resolved by developing hybridization process like combining biometrics template with user knowledge keys or passwords for secure authentication. The challenges in template protection are like alignment of template, selection of pseudonymous identifiers (PI), and auxiliary data (AD). An attempt is made to review the literature in this direction and present few issues and challenges in the field of biometric template protection.

In this paper, a proposed cancellable biometric scheme is based on multiple biometric image identifiers, Arnold’s cat map and double random phase encoding (DRPE) to obtain cancellable biometric templates. The proposed segmentation scheme that is used to select the region of interest for generating cancelable templates is based on chaos entropy low correlation statistical metrics. The objective of segmentation is to reduce the computational cost and reliability of template creation. The left and right biometric (iris, fingerprint, palm print and face) are divided into non-overlapping blocks of the same dimensions. To define the region of interest (ROI), we select the block with the highest entropy. To shorten the registration process time and achieve a high level of security, we select 25% of the image volume of the biometric data. In addition, the low-cost security requirement lies in the use of selective encryption (SE) technology. The step of selecting the maximum entropy is executed on all biometric blocks. The maximum right and left multi-biometric blocks are arranged in descending order from the entropy perspective and select 50% of each biometric couple and store the single matrix. The obtained matrix is scrambled with a certain number of iterations using Arnold’s Cat Map (ACM).The obtained scrambled matrix is encrypted with the DRPE to generate the cancellable biometric templates, which are further concatenated. The simulation results display better performance of the suggested cancellable biometric system in noise scenarios using the area under the receiver operating characteristic (AROC). The strength of the suggested technique is examined with correlation, irregular deviation, maximum difference and maximum deviation. The recommended proposed approach shows that the ability to distinguish the authentic and imposter biometrics of user seven in different levels of the noise environment.

With the advancement of multimedia technology and coming of big data era, the size of image data is significantly increased. However, the traditional image encryption methods cannot solve the emerging problems of efficient compression. To settle with this challenge, an effective content-adaptive image compression and encryption method based on compressive sensing and double random phase encoding (DRPE) is proposed in this paper. The original image is converted to one low-frequency part and three high-frequency parts by DWT and then permutated by sorting-based chaotic sequences. Afterward, a novel measurement matrix optimization algorithm based on adaptive step size is presented to measure the high-frequency components. To enhance the security of the scheme, the DRPE, quantization, and diffusion are successively performed on the complex matrix composed of the shuffled low-frequency component and three measurement value matrices to obtain the cipher image. Logistic-Sine chaotic system is utilized to produce the chaotic keystreams for the encryption process, and its system parameter and initial value are determined by the information entropy of the plain image and external key parameters, so that the proposed cipher can withstand known-plaintext and chosen-plaintext attacks effectively. Numerical experiments demonstrate the effectiveness of the proposed image compression and encryption algorithm.

Background: Among optical encryption techniques, Double Random Phase Encoding (DRPE) is one of the most widely used. Individual identities and the process of recognition remain essential to ensuring proper data access security.Aim: The study aims to optimize an approach that ensures the significant performance effectiveness of the cancelable biometric methods for different templates and the associated time taken to transform biometric data.Problem: This study is majorly concerned about the performance effectiveness of cancelable biometric methods that measure the likelihood that an authorized effort may be mistakenly rejected as unauthorized. Also, when compromised, several non-renewability safety challenges arise, and insufficient matching performance templates are required to build a security protection method.Method and material. The study uses supervised learning for the Double Random Phase Encoding Method (DRPE), a 4F optical encryption system, and 20 randomly chosen photos from the ORL database of faces.Results. The result based on the supervised learning for the Double Random Phase Encoding Method revealed false positive rates for both the fingerprint and face templates.Conclusion. The study concluded that the performance effectiveness of the cancelable biometric in this study has a false positive rate likelihood that an authorized effort may not be mistakenly rejected as an unauthorized one.

Compared with digital methods, image hiding methods by optical ways have many advantages such as high processing speed, high parallel, high encryption dimension etc al. A novel efficient image encryption and hiding method applied by double random phase encoding technique is discussed in this paper. First, the performance of existing optical image hiding systems is analyzed; then specific statistical detection methods to the optical image hiding system are discussed; then extracting attacks to the optical image hiding system are analyzed; finally novel optical image hiding methods by technique of double random phase encoding and digital holography are given out.

Double random phase encoding (DRPE) is a typical optical encryption technique, in which the cipher key is allowed to include redundancy between encryption and decryption. It has been shown that phase-only DRPE has the robust to known-plaintext attacks using a phase retrieval algorithm. In addition, it has been also shown that phase only DRPE can decrypt the encrypted image successfully with the singular key that is completely different from the encryption key. In this study, we analyzed the distribution of the key-space in the phase-only DRPE by means of calculating the Euclidean distance between the decryption key and the encryption key and counting the number of the correct decryption keys. As a result of the experiments, we confirmed that the distribution property of the correct keys in the phase-only DRPE is significantly different from the one in the conventional DRPE.

In recent years, the speaker recognition technology is significant system for securing the biometric authentication and enabling remote logins for telephone banking and enterprise applications. Whereas Speech Signal Detection ensure with accurate speaker identification and verification for restricted access and sensitive data protection. The combination of speaker recognition technology with speech signal detection has accompanied in a new era of biometric authentication, providing unparalleled security and accuracy in verifying identities. However, Vulnerability to voice spoofing attacks leads to imitation of speaker such as mimicry or synthetic speech, compromise system security. To overcome these drawbacks, an Optical Scanning Holography with Double Random Phase Encoding (OSH-DRPE) is proposed using Texas Instruments Massachusetts Institute of Technology (TIMIT) dataset. After collecting the data, the data is preprocessed through normalization approaches for normalize the data. Then, a Mel-Frequency Cepstral Coefficients (MFCC) is employed for feature extraction to extract relevant features, which produces low computational complexity. At last, OSH-DRPE is used as classifier to detect speech signal and speaker recognition with higher accuracy, efficient computation and flexibility. From the results, it clearly shows that the proposed OSH-DRPE obtained higher values in the context of precision, F1 score and accuracy when compared to existing Hidden Markov Model (HMM).