In this paper, we have recently created self-driving cars and self-parking systems in human-friendly that can provide high safety convenience functions by recognizing the internal external situations of automobiles real time incorporating next-generation electronics, information communication, function control technologies. And with development connected cars, ITS (Intelligent Transportation Sy...

The value of trajectory data lies mainly in the spatio-temporal correlation. However, existing privacy protection methods ignore correlation data, resulting a large error proportion estimation and Top-K classification. For truck intelligent logistics, location perturbation method based on quadtree indexing is proposed, which leverages generalization local differential techniques. Our proposed a...

Current network protection systems use a collection of intelligent components e.g. classifiers or rule-based firewall systems to detect intrusions and anomalies and to secure a network against viruses, worms, or trojans. However, these network systems rely on individuality and support an architecture with less collaborative work of the protection components. They give less administration suppor...

Current network protection systems use a collection of intelligent components e.g. classifiers or rule-based firewall systems to detect intrusions and anomalies and to secure a network against viruses, worms, or trojans. However, these network systems rely on individuality and support an architecture with less collaborative work of the protection components. They give less administration suppor...

Intelligent surveillance is becoming increasingly important for the enhanced protection of facilities such as airports and power stations from various types of threats. We propose a surveillance system architecture based on multiple sources of information to apply on large scale surveillance networks. The main contribution of this paper is the definition of the requirements for a flexible and s...

An intelligent strategy for the protection of AC microgrids is presented in this paper. This method was halving to an initial signal processing step and a machine learning-based forecasting step. The initial stage investigates currents and voltages with a window-based approach based on the dynamic decomposition method (DDM) and then involves the norms of the signals to the resultant DDM data. T...