In the world of digital communication, Authentication is an important concern and the need for a safe and secure System increases the necessity of designing Authentication Systems. To perform Authentication, biometric-based approaches are of great interest due to the property of being alive and resistant to forgery. In this study, an Authentication System based on heart signal is designed. Due to the process of receiving heart signals, their data usually has a lot of noise. In order to prepare the data, in the proposed System, the heart signals are first cleaned and then transferred to the frequency domain for feature extraction. Also, they are converted into an image by applying the Wigner-Ville distribution, so that each image contains the signal information of each person’s heart and is unique. In the proposed Authentication System, these images are used for training and evaluation in a deep convolutional neural network. The output of this System provides the possibility of people’s identification. The data of this study are taken from the NSRDB and MITDB databases, and significant results have been obtained compared to previous studies.

Security is a vital issue in the usage of Automated Teller Machine (ATM) for cash, cashless and many off the counter banking transactions. Weaknesses in the use of ATM machine could not only lead to loss of customer’ s data confidentiality and integrity but also breach in the verification of user’ s Authentication. Several challenges are associated with the use of ATM smart card such as: card cloning, card skimming, cost of issuance and maintenance. In this paper, we present secure bio-cryptographic Authentication System for cardless ATM using enhanced fingerprint biometrics trait and encrypted Personal Identification Number (PIN). Fingerprint biometrics is used to provide automatic identification/verification of a legitimate customer based on unique feature possessed by the customer. Log-Gabor filtering algorithm was used for enhancing low image quality and effect of noise on feature extracted from customer’ s fingerprint minutiae. Truncated SHA 512/256 hash algorithm was used to secure the integrity and confidentiality of the PIN from sniffers and possible adversary within the channel of remote ATM banking transactions. Performance evaluation was carried out using False Acceptance Rate (FAR), False Rejection Rate (FRR) metrics and Collision Attack was performed on the Truncated SHA-512/256 hashed data (PIN). Results of the System performance shows Genuine Acceptance Rate (1-FRR) of 97. 5% to 100%, Equal Error Rate of 0. 0015% and Collision Attack carried out on the encrypted PIN message digest gave an unsuccessful attack. Therefore, the results of performance evaluation show the applicability of the developed System for secure cardless ATM transaction.

Background and Purpose: Identifying authenticity of vehicles one of the issues emphasized by the experts of numbering and plate changing units, and various reasons may change the authenticity of vehicles, which is unavoidable in some cases, according to the laws of the country. Changes in components of vehicles are examples of such a crimes. The purpose of current research is to identify damages of verifying authenticity of vehicles.Method: This research is an exploratory mixed method in terms of practical purpose. In qualitative part, the statistical population was interviews with the experts of traffic police headquarters using a purposeful sampling method, and quantitative part, statistical population was based numbering experts of Tehran province using a stratified method. qualitative part of the theme analysis method was used using MAXQDA2020 software quantitative part, confirmatory factor analysis was used, validate model obtained from the qualitative part, structural equation modeling was used using pls3 Smart confirmatory factor analysis software.Findings: The greatest effect of vehicle Authentication pathology quantitative section related to the dimension of behavioral injuries with a value of 24.361, and then related to dimension of contextual injuries with a value of 17.753, finally, the least impact is related to dimension Structural damage with a value of 4.641 is in Results: With the increase in the number of vehicles and the progress science and technology, need to recognize the damage of authenticating vehicles control and monitor performance of drivers and owners of vehicles using specialized equipment in field of authenticating has become inevitable.