An efficient anonymous authentication protocol in multiple server communication networks (EAAM)

In a multi-server authentication environment, a user only needs to register once at a central registration place before accessing the different services on the different registered servers. Both, from a user point of view as for the management and maintenance of the infrastructure, these types of environments become more and more popular. Smartcard- or smartphone-based approaches lead to more secure systems because they offer two- or three-factor authentication, based on the strict combination of the user’s password, the user’s biometrics and the possession of the device. In this paper, we propose an efficient anonymous authentication protocol in multiple server communication networks, called the EAAM protocol, which is able to establish user anonymity, mutual authentication, and resistance against known security attacks. The novelty of the proposed scheme is that it does not require a secure channel during the registration between the user and the registration center and is resistant to a curious but honest registration system. These features are established in a highly efficient way with the minimum amount of communication flows between user and server during the establishment of the secret shared key and by using light-weight cryptographic techniques such as Chebyshev chaotic map techniques and symmetric key cryptography. The performance and security of the protocol are analyzed and compared with the latest new proposals in this field.     

Evaluation of turbo and hydro‐generator torques due to electromechanical interaction

Abstract

The computer prediction of turbogenerator behaviour following fault or disturbance conditions has become an important feature in the assessment of machine system design, pre‐commissioning test appraisals, system operational procedures, machine monitoring strategy and post‐event damage diagnoses. In this paper computer methods are described to assess the comparative severity of various electrical faults and disturbances, the effect of specific operational practices together with the prediction of peak torsional transient behaviour. This paper is supported by realistic examples simulating the transient behaviour of a number of generational units.     

Using self‐constructing recurrent fuzzy neural network as a digital channel equalizer

Abstract

In this paper the design of a self‐constructing recurrent fuzzy neural network (SCRFNN)‐based digital channel equalizer is proposed. It is found that a digital channel equalizer based on SCRFNN can recover channel distortions effectively. We compare the performance of SCRFNN with adaptive‐based‐network fuzzy inference system (ANFIS) and the Bayesian equalizers in complex‐valued linear channels. Our simulations show that the performance of SCRFNN is close to the Bayesian optimal solution. Furthermore, the hardware requirement of the trained SCRFNN equalizer is relatively lower than the other two structures.