A novel certificateless deniable authentication protocol

Deniable authenticated protocol is a new and attractive protocol compared to the traditional authentication protocol. It allows the appointed receiver to identify the source of a given message, but not to prove the identity of the sender to a third party even if the appointed receiver is willing to reveal its private key. In this paper, we first define a security model for certificateless deniable authentication protocols. Then we propose a non-interactive certificateless deniable authentication protocol, by combining deniable authentication protocol with certificateless cryptography. In addition, we prove its security in the random oracle model

Automation and Robotics: Latest Achievements, Challenges and Prospects

This SI presents the latest achievements, challenges and prospects for drives, actuators, sensors, controls and robot navigation with reverse validation and applications in the field of industrial automation and robotics. Automation, supported by robotics, can effectively speed up and improve production. The industrialization of complex mechatronic components, especially robots, requires a large number of special processes already in the pre-production stage provided by modelling and simulation. This area of research from the very beginning includes drives, process technology, actuators, sensors, control systems and all connections in mechatronic systems. Automation and robotics form broad-spectrum areas of research, which are tightly interconnected. To reduce costs in the pre-production stage and to reduce production preparation time, it is necessary to solve complex tasks in the form of simulation with the use of standard software products and new technologies that allow, for example, machine vision and other imaging tools to examine new physical contexts, dependencies and connections

Machine learning based learner modeling for adaptive web-based learning

International Conference on Computational Science and its Applications, ICCSA 2007; Kuala Lumpur; Malaysia; 26 August 2007 through 29 August 2007Especially in the first decade of this century, learner adapted interaction and learner modeling are becoming more important in the area of web-based learning systems. The complicated nature of the problem is a serious challenge with vast amount of data available about the learners. Machine learning approaches have been used effectively in both user modeling, and learner modeling implementations. Recent studies on the challenges and solutions about learner modeling are explained in this paper with the proposal of a learner modeling framework to be used in a web-based learning system. The proposed system adopts a hybrid approach combining three machine learning techniques in three stages