The shadows similar to the vehicle and the spots caused by vehicle lamps need to be accurately detected in the vehicle segmentation involved in the video-based traffic parameter measurement. Generally, the road surfac...The shadows similar to the vehicle and the spots caused by vehicle lamps need to be accurately detected in the vehicle segmentation involved in the video-based traffic parameter measurement. Generally, the road surface is different from the vehicle surface in the gray-level architecture. An invariant gray-level architecture-the extremum image in the changing illumination environment is derived and a novel algorithm is presented for detecting shadows and spots. The gray-level structure that is not sensitive to the illumination is employed in the algorithm and the road surface mistaken as vehicles can be removed.展开更多
Wireless Mesh Networks is vulnerable to attacks due to the open medium, dynamically changing network topology, cooperative algorithms, Lack of centralized monitoring and management point. The traditional way of protec...Wireless Mesh Networks is vulnerable to attacks due to the open medium, dynamically changing network topology, cooperative algorithms, Lack of centralized monitoring and management point. The traditional way of protecting networks with firewalls and encryption software is no longer suffi- cient and effective for those features. In this paper, we propose a distributed intrusion detection ap- proach based on timed automata. A cluster-based detection scheme is presented, where periodically a node is elected as the monitor node for a cluster. These monitor nodes can not only make local intrusion detection decisions, but also cooperatively take part in global intrusion detection. And then we con- struct the Finite State Machine （FSM） by the way of manually abstracting the correct behaviors of the node according to the routing protocol of Dynamic Source Routing （DSR）. The monitor nodes can verify every node＇s behavior by the Finite State Ma- chine （FSM）, and validly detect real-time attacks without signatures of intrusion or trained data.Compared with the architecture where each node is its own IDS agent, our approach is much more efficient while maintaining the same level of effectiveness. Finally, we evaluate the intrusion detection method through simulation experiments.展开更多
The topological structure of a complex dynamical network plays a vital role in determining the network＇s evolutionary mecha- nisms and functional behaviors, thus recognizing and inferring the network structure is of ...The topological structure of a complex dynamical network plays a vital role in determining the network＇s evolutionary mecha- nisms and functional behaviors, thus recognizing and inferring the network structure is of both theoretical and practical signif- icance. Although various approaches have been proposed to estimate network topologies, many are not well established to the noisy nature of network dynamics and ubiquity of transmission delay among network individuals. This paper focuses on to- pology inference of uncertain complex dynamical networks. An auxiliary network is constructed and an adaptive scheme is proposed to track topological parameters. It is noteworthy that the considered network model is supposed to contain practical stochastic perturbations, and noisy observations are taken as control inputs of the constructed auxiliary network. In particular, the control technique can be further employed to locate hidden sources （or latent variables） in networks. Numerical examples are provided to illustrate the effectiveness of the proposed scheme. In addition, the impact of coupling strength and coupling delay on identification performance is assessed. The proposed scheme provides engineers with a convenient approach to infer topologies of general complex dynamical networks and locate hidden sources, and the detailed performance evaluation can further facilitate practical circuit design.展开更多
文摘The shadows similar to the vehicle and the spots caused by vehicle lamps need to be accurately detected in the vehicle segmentation involved in the video-based traffic parameter measurement. Generally, the road surface is different from the vehicle surface in the gray-level architecture. An invariant gray-level architecture-the extremum image in the changing illumination environment is derived and a novel algorithm is presented for detecting shadows and spots. The gray-level structure that is not sensitive to the illumination is employed in the algorithm and the road surface mistaken as vehicles can be removed.
基金Acknowledgements Project supported by the National Natural Science Foundation of China （Grant No.60932003）, the National High Technology Development 863 Program of China （Grant No.2007AA01Z452, No. 2009AA01 Z118 ）, Project supported by Shanghai Municipal Natural Science Foundation （Grant No.09ZRI414900）, National Undergraduate Innovative Test Program （091024812）.
文摘Wireless Mesh Networks is vulnerable to attacks due to the open medium, dynamically changing network topology, cooperative algorithms, Lack of centralized monitoring and management point. The traditional way of protecting networks with firewalls and encryption software is no longer suffi- cient and effective for those features. In this paper, we propose a distributed intrusion detection ap- proach based on timed automata. A cluster-based detection scheme is presented, where periodically a node is elected as the monitor node for a cluster. These monitor nodes can not only make local intrusion detection decisions, but also cooperatively take part in global intrusion detection. And then we con- struct the Finite State Machine （FSM） by the way of manually abstracting the correct behaviors of the node according to the routing protocol of Dynamic Source Routing （DSR）. The monitor nodes can verify every node＇s behavior by the Finite State Ma- chine （FSM）, and validly detect real-time attacks without signatures of intrusion or trained data.Compared with the architecture where each node is its own IDS agent, our approach is much more efficient while maintaining the same level of effectiveness. Finally, we evaluate the intrusion detection method through simulation experiments.
基金supported by the National Science and Technology Major Project of China(Grant No.2014ZX10004001-014)the National Natural Science Foundation of China(Grant Nos.61573262,61532020&11472290)the Fundamental Research Funds for the Central Universities(Grant No.2014201020206)
文摘The topological structure of a complex dynamical network plays a vital role in determining the network＇s evolutionary mecha- nisms and functional behaviors, thus recognizing and inferring the network structure is of both theoretical and practical signif- icance. Although various approaches have been proposed to estimate network topologies, many are not well established to the noisy nature of network dynamics and ubiquity of transmission delay among network individuals. This paper focuses on to- pology inference of uncertain complex dynamical networks. An auxiliary network is constructed and an adaptive scheme is proposed to track topological parameters. It is noteworthy that the considered network model is supposed to contain practical stochastic perturbations, and noisy observations are taken as control inputs of the constructed auxiliary network. In particular, the control technique can be further employed to locate hidden sources （or latent variables） in networks. Numerical examples are provided to illustrate the effectiveness of the proposed scheme. In addition, the impact of coupling strength and coupling delay on identification performance is assessed. The proposed scheme provides engineers with a convenient approach to infer topologies of general complex dynamical networks and locate hidden sources, and the detailed performance evaluation can further facilitate practical circuit design.
