Remote data auditing (RDA) protocols enable a cloud server to persuade an auditor that it is storing a data file honestly. Unlike digital signature (DS) schemes, in RDA protocols, the auditor can carry out the auditing procedure without having the entire data file. Therefore, RDA protocols seem to be attractive alternatives to DSs as they can effectively reduce bandwidth consumption. However, existing RDA protocols do not provide adequately powerful tools for user Authentication. In this paper, we put forward a novel Attribute-Based remote data auditing and user Authentication scheme. In our proposed scheme, without having a data file outsourced to a cloud server, an auditor can check its integrity and the issuer’, s authenticity. Indeed, through a challenge-response protocol, the auditor can check whether 1) the cloud server has changed the content of the data file or not,2) the data owner possesses specific Attributes or not. We show that our scheme is secure under the hardness assumption of the bilinear Diffie-Hellman (BDH) problem.

The smart home is an important Internet of Things applications. Due to the smartphones development, expansion of their network, and growing the data transfer rate, security in personal life has become a dramatic challenge. Therefore, it is essential to secure such a system to create a sense of relaxation in the lives of users and homeowners to deal with possible occurrences. The integration of technologies for the automation of home affairs with the Internet of things means that all physical objects can be accessed on cyberspace; therefore, the concerns raised by users about the lack of privacy and security are serious arguments that science and technology should answer. Therefore, addressing security issues is a crucial necessity for the development of the smart homes. Although Authentication protocols have been proposed Based on smart cards for multi-server architectures, their schemes cannot protect the system against stolen smart cards and dictionary attacks in the login phase and do not satisfy perfect forward secrecy. To overcome these limitations, this paper proposes an anonymous, secure protocol in connected smart home environments, using solely lightweight operations. The proposed protocol in this paper provides efficient Authentication, key agreement, and enables the anonymity of devices and unlinkability. It is demonstrated that the computation complexity of the protocol is low as compared to the existing schemes, while security has been significantly improved. This protocol ensures that even if the stakeholder’ s device or the IoT device is attacked, they are robust against them.

Nowadays, fast and accurate algorithms for signature verification are very attractive. In the area of dynamic signature verification, the features are classified into two groups: parametric and functional features. In parametric algorithms, although the speed of features extraction and classification process is faster than function Based approaches but they are less accurate. The goal of this paper is modeling of the velocity signal that its pattern and properties are stable for a person. With using pole-zero models Based on discrete cosine transform, a precise method is proposed for modeling and then features are extracted from strokes. These features are the deference of pole angles of strokes. Applying linear, parzen window and support vector machine classifiers, the proposed algorithm was tested on data set from Persian, Chinese, English and Turkish people and with common threshold, resulted equal error rates of 1.25% and 1.78% in the random and skilled forgeries, respectively.

This research investigates the utilization of machine learning techniques for the identification and classification of counterfeit currency. The study utilizes a dataset consisting of authentic and counterfeit banknotes, employing various classification algorithms to construct a robust model for automated detection. Key features, including texture, color distribution, and security Attributes, are extracted to train the model, enabling a thorough analysis of banknote authenticity. The proposed system exhibits promising accuracy in distinguishing genuine currency from counterfeits, thereby enhancing security measures in financial transactions and mitigating economic fraud.