• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2178-2181
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• 2003

Active networks allow active node’s functionality to be extended dynamically through the use of active extensions. This flexible architecture facilitates the deployment of new network protocols and services. However, the active nature of a network also raises serious safety and security concerns. These concerns must be addressed before active networks can be deployed. In this paper we look at how we can control active extension’s access to different active nodes. Specifically, the authentication between active nodes is very important in this case. We use unique identity each node has for transferring access policies between active nodes. In this paper, we suggest a new method of transferring access policies performing authentications using identities between active nodes.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.941-946
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• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• Journal of KIISE:Information Networking
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• v.29 no.5
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• pp.510-523
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• 2002

The routers in an active network perform customized computations on the messages flowing through them, while the role of routers in the traditional packet network, such as the Internet, is to passively forward packets as fast as possible. In contrast to the Internet, the processing in active networks can be customized on a per user or per application basis. Active networks allow users to inject information into the network, where the information describes or controls a program to be executed for the users by the routers as well as the end hosts. So the network users can realize the active networks by "programming" the network behavior via the programming interface exposed to them. In this paper, we devise a network protocol model and present a verification technique for reasoning about the correctness of an active application defined using the model. The technique is developed in a platform- and language-independent way, and it is algorithmic and can be automated by computer program. We give an example dealing with network auction to illustrate the use of the model and the verification technique.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.4 s.304
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• pp.17-24
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• 2005

The existing passive networks have the only data-storing and transmission functions. On the other hand, the active network which can do operation jobs on the transmitting packets was introduced at 1990's. However, the advantages of activating processing are obviously more complex than traditional networks and raise considerable security issues. In this paper, we propose the safer structure in Active Networks that is based on the discrete approach which resolves the weak point of the Active Network. The proposed system provides the node management and user management in the Active Networks, and improves the security of Packet transmission with packet cryptography and the session.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.4
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• pp.29-38
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• 2020

In this research, we proposed the active pulse classification algorithm using multi-label convolutional neural networks for active sonar system. The proposed algorithm has the advantage of being able to acquire the information of the active pulse at a time, unlike the existing single label-based algorithm, which has several neural network structures, and also has an advantage of simplifying the learning process. In order to verify the proposed algorithm, the neural network was trained using sea experimental data. As a result of the analysis, it was confirmed that the proposed algorithm converged, and through the analysis of the confusion matrix, it was confirmed that it has excellent active pulse classification performance.

• Journal of Communications and Networks
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• v.11 no.4
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• pp.406-415
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• 2009

In this work, we consider performance modeling of a wireless sensor network with a time division multiple access (TDMA) media access protocol with slot reuse. It is assumed that all the nodes are peers of each other and they have two modes of operation, active and sleep modes. We model the sensor network as a Jackson network with unreliable nodes with on and off states. Active and sleep modes of sensor nodes are modeled with on and off states of unreliable nodes. We determine the joint distribution of the sensor node queue lengths in the network. From this result, we derive the probability distribution of the number of active nodes and blocking probability of node activation. Then, we present the mean packet delay, average sleep period of a node and the network throughput. We present numerical results as well as simulation results to verify the analysis. Finally, we discuss how the derived results may be used in the design of sensor networks.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.932-940
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• 1999

In this paper, a new neural networks and neural network based sliding mode controller are proposed. The new neural networks are an mor self-recurrent neural networks which use a recursive least squares method for the fast on-line leammg. The error self-recurrent neural networks converge considerably last than the back-prollagation algorithm and have advantage oi bemg less affected by the poor initial weights and learning rate. The controller for suspension system is designed according to sliding mode technique based on new proposed neural networks. In order to adapt shding mode control mnethod, each frame dstance hetween ground and vehcle body is estimated md controller is designed according to estimated neural model. The neural networks based sliding mode controller approves good peiformance throllgh computer sirnulations.

• The KIPS Transactions:PartC
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• v.10C no.4
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• pp.413-422
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• 2003

An active network is a new generation network based on a software-intensive network architecture in which applications are able to inject new strategies or code into the infrastructure for their immediate needs. Therefore, the secure active node architecture is needed to give the capability defending an active node against threats that may be more dynamic and powerful than those in traditional networks. In this paper, a security enforcement engine is proposed to secure active networks. We implemented an operating engine with security, authentication and a authorization modules. Using this engine, it is possible that active networks are protected from threats of the malicious active node.

• Journal of Korea Multimedia Society
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• v.21 no.9
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• pp.1062-1067
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• 2018

Conventional active sonar technology has relied heavily on the hearing of sonar operator, but recently, many techniques for automatic detection and classification have been studied. In this paper, we extract the image data from the spectrogram of the active sonar signal and classify the extracted data using CNN(convolutional neural networks), which has recently presented excellent performance improvement in the field of pattern recognition. First, we divided entire data set into eight classes depending on the ratio containing the target. Then, experiments were conducted to classify the eight classes data using proposed CNN structure, and the results were analyzed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.2
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• pp.135-145
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• 2002

Active networks represent a new approach to network architecture. Nodes(routers, switches, etc.) can perform computations on user data, while packets can carry programs to be executed on nodes and potentially change the state of them. While active networks provide a flexible network iufrastructure, they are more complex than traditional networks and raise considerable security problems. Nodes are Public resources and are essential to the proper and contract running of many important systems. Therefore, security requirements placed upon the computational environment where the code of packets will be executed must be very strict. Trends of research for active network security are divided into two categories: securing active nodes and securing active packets. For example, packet authentication or monitoring/control methods are for securing active node, but some cryptographic techniques are for the latter. This paper is for transferring active packets securely between active nodes. We propose a new method that can transfer active packets to neighboring active nodes securely, and execute executable code included in those packets in each active node. We use both public key cryptosystem and symmetric key cryptosystem in our scheme