• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.197-206
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• 2003

With the growing usage of the networks, the world-wide Internet has become the main means to exchange data and carry out transactions. It has also become the main means to attack hosts. To solve the security problems which occur in the network such as Internet, we import software products of network security elements like an IDS (Intrusion Detection System) and a firewall. In this paper, we have designed and constructed the General Simulation Environment of Network Security model composed of multiple IDSes and a firewall which coordinate by CNP (Contract Net Protocol) for the effective detection of the intrusion. The CNP, the methodology for efficient integration of computer systems on heterogeneous environment such as distributed systems, is essentially a collection of agents, which cooperate to resolve a problem. Command console in the CNP is a manager who controls tie execution of agents or a contractee, who performs intrusion detection. In the Network Security model, each model of simulation environment is hierarchically designed by DEVS (Discrete EVent system Specification) formalism. The purpose of this simulation is to evaluate the characteristics and performance of CNP architecture with rete pattern matching algorithm and the application of rete pattern matching algorithm for the speeding up the inference cycle phases of the intrusion detection expert system.

• Journal of IKEEE
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• v.25 no.4
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• pp.756-761
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• 2021

Dynamic route guidance (DRG) finds the fastest path from a source to a destination location considering the real-time congestion information. In Korea, the traffic state information is available by the public transportation data (PTD) which is indexed on top of the node-link map (NLM). While the NLM is the authoritative low-detailed road network for major roads only, the OpenStreetMap road network (ORN) supports not only a high-detailed road network but also a few open-source routing engines, such as OSRM and Valhalla. In this paper, we propose a DRG framework based on road network matching between the NLM and ORN. This framework regularly retrieves the NLM-indexed PTD to construct a historical speed profile which is then mapped to ORN. Next, we extend the Valhalla routing engine to support dynamic routing based on the historical speed profile. The numerical results at the Yeoui-do island with collected 11-month PTD show that our DRG framework reduces the travel time up to 15.24 % and improves the estimation accuracy of travel time more than 5 times.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.343-364
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• 2021

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.9
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• pp.661-667
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• 2018

Tactical communication radio systems that employ software defined radios(SDRs) have been developed for achieving high-speed data transmissions and voice communications. Such systems possess multiband and multichannel features, and can potentially replace several existing radio systems. This paper proposes a design for wideband antennas by incorporating a diplexer matching network for tactical vehicles. The proposed antenna design includes two radiators(upper and lower) and a diplexer matching network connected to the end of the feed line such that the LC matching networks are interleaved in the lower radiator and spring mount. By employing the diplexer matching network, the designed antenna can perform wideband impedance matching for the fifty ohm feed line. The designed LC networks aid in varying the effective electrical length of the antenna according to the operation frequency. The primary objective behind adjusting the electrical length is to vary the current distribution above and below the LC networks. The proposed antenna was fabricated and tested in an open site. The obtained evaluation results show that the designed antenna can achieve a relative bandwidth of 190% with a VSWR value of 3.5:1, and can attain good antenna gains over VHF and UHF bands.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1B
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• pp.47-55
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• 2009

In recent network intrusion detection systems, regular expressions are used to represent malicious packets. In order to process incoming packets through high speed networks in real time, we should perform hardware-based pattern matching using the configurable device such as FPGAs. However, operating speed of FPGAs is slower than giga-bit speed network and so, multi-byte processing per clock cycle may be needed. In this paper, we propose a hardware architecture of multi-byte based regular expression pattern matching and implement the pattern matching circuit generator. The throughput improvements in four-byte based pattern matching circuit synthesized in FPGA for several Snort rules are $2.62{\sim}3.4$ times.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.8
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• pp.1913-1925
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• 2012

In order to efficiently utilize limited radio resources, resource allocation schemes in OFDMA-based wireless networks have gained intensive attention recently. Instead of improving the throughput performance, the utility is adopted as the metric for resource allocation, which provides reasonable methods to build up the relationship between user experience and various quality-of-service (QoS) metrics. After formulating the optimization problem by using a weighted bipartite graph, a modified bipartite matching method is proposed to find a suboptimal solution for the resource allocation problem in OFDMA-based wireless systems with feasible computational complexity. Finally, simulation results are presented to validate the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.306-309
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• 1996

This paper presents a method of landmark recognition in indoor environments using a neural-network for an autonomous mobile robot. In order to adapt to image deformation of a landmark resulted from variations of view-points and distances, a multi-labeled template matching(MLTM) method and a dynamic area search method(DASM) are proposed. The MLTM is. used for matching an image template with deformed real images and the DASM is proposed to detect correct feature points among incorrect feature points. Finally a feed-forward neural-network using back-propagation algorithm is adopted for recognizing the landmark.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05c
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• pp.194-199
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• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The proposed neural network technique is the real time computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objects during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of objects. All of them request much memory space and time. Therefore the most reliable neural-network algorithm is derived for real-time matching of objects, which is composed of a dynamic programming algorithm based on sequence matching techniques.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.79-90
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• 2008

In the ubiquitous environment sensor network technologies have advanced for collecting information of the environment. With the rapid growth of sensor network technology, it is necessary and important to share the collected sensor data with a large base of diverse users. In order to provide dissemination of sensor data, we design an information dissemination system using an independent disseminator between provider and consumer. This paper describes how we designed the information dissemination system using one of the possible dissemination patterns for sensor networks, and an efficient matching algorithm called CGIM (Classed Grouping Index Matching) which employs a dynamic re-grouping scheme.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.69-76
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• 2018

Referring expressions are natural language constructions used to identify particular objects within a scene. In this paper, we propose a new deep neural network model for referring expression comprehension. The proposed model finds out the region of the referred object in the given image by making use of the rich information about the referred object itself, the context object, and the relationship with the context object mentioned in the referring expression. In the proposed model, the object matching score and the relationship matching score are combined to compute the fitness score of each candidate region according to the structure of the referring expression sentence. Therefore, the proposed model consists of four different sub-networks: Language Representation Network(LRN), Object Matching Network (OMN), Relationship Matching Network(RMN), and Weighted Composition Network(WCN). We demonstrate that our model achieves state-of-the-art results for comprehension on three referring expression datasets.