• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.1-13
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• 2009

Intrusion detection is a process that identifies the attacks and responds to the malicious intrusion actions for the protection of the computer and the network resources. Due to the fast development of the Internet, the types of intrusions become more complex recently and need immediate and correct responses because the frequent occurrences of a new intrusion type rise rapidly. Therefore, to solve these problems of the intrusion detection systems, we propose a sequential pattern miner for analysis of the alert data in order to support intelligent and automatic detection of the intrusion. Sequential pattern mining is one of the methods to find the patterns among the extracted items that are frequent in the fixed sequences. We apply the prefixSpan algorithm to find out the alert sequences. This method can be used to predict the actions of the sequential patterns and to create the rules of the intrusions. In this paper, we propose an extended prefixSpan algorithm which is designed to consider the specific characteristics of the alert data. The extended sequential pattern miner will be used as a part of alert data analyzer of intrusion detection systems. By using the created rules from the sequential pattern miner, the HA(high-level alert analyzer) of PEP(policy enforcement point), usually called IDS, performs the prediction of the sequence behaviors and changing patterns that were not visibly checked.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.807-816
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• 2005

Sequential pattern mining finds all of the frequent sequences satisfying a minimum support threshold in a large database. However, when mining long frequent sequences, or when using very low support thresholds, the performance of currently reported algorithms often degrades dramatically. In this paper, we propose a novel sequential pattern algorithm using only closed frequent sequences which are small subset of very large frequent sequences. Our algorithm generates the candidate sequences by depth-first search strategy in order to effectively prune. using bitmap representation of underlying databases, we can effectively calculate supports in terms of bit operations and prune sequences in much less time. Performance study shows that our algorithm outperforms the previous algorithms.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.198-205
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• 2013

In this paper, the performance of multicore processor architecture is analyzed which utilizes out-of-order superscalar processor core using multiple basic block execution. Using SPEC 2000 benchmarks as input, the trace-driven simulation has been performed for the out-of-order superscalar processor with the window size from 32 to 64 and the number of cores between 1 and 16, exploiting multiple basic block execution from 1 to 4 extensively. As a result, the multicore out-of-order superscalar processor with 4 basic block execution achieves 22.0 % average performance increase over the same architecture with the single basic block execution.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.73-83
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• 2015

This paper proposes a TFT-LCD defect blob detection algorithm using the sequential defect detection method. First, for every pixel, a defect possibility is determined by the intensity difference and the defect candidates are detected according to the sequential defect detection method. For detected candidate pixels, the defect probability that indicates a potential included in the defect according to the each step. By applying the morphological operation, blobs are comprised of the detected candidates and the defect blobs are detected using the defect possibility of blobs. The validity of the proposed method was demonstrated a simulated image and also then it was tested a real TFT-LCD image. By the experimental results, the proposed method is very effective in TFT-LCD detect detection.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.217-226
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• 2003

A novel fingerprint ridge feature extraction using sequential labeling of thinned fingerprint image is proposed, which is invariant to position translation, scaling, and rotation. the proposed algorithm labels ridges of thinned fingerprint image sequentially using vertical line that goes through fingerprint core point. Then, we extract a feature from each labeled ridge and the extraction process is based on the type fo the ridge and a minutiae ridge angle in the ridge. The feature extracted through this process enables us to find out the kind of various minutiae and minutiae angle. As a result of the experiment using two thinned fingerprint images, we finally confirm that proposed algorithm is not related to position translation, scaling, and rotation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.8
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• pp.1-6
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• 2002

In this paper, we considered the CDMA/TDD system suitable for high-speed packet data transmission such as Internet and multimedia services, and a sequential decoding scheme which enables fast decoding and retransmission requirement. In addition, we Proposed an improved FANO algorithm, which adopts the competition path in order to reduce the number of revisit nodes. The conventional FANO algorithm suffered from the drawback of much more revisit nodes. Furthermore, we analyzed the performance of the CDMA/TDD system with the sequential decoding scheme we proposed over multipath channel.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1249-1257
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• 2011

In this paper, we propose a Sequential Adaptive Nearest Neighbor(SANN) imputation method that combines the Adaptive Nearest Neighbor(ANN) method and the Sequential k-Nearest Neighbor(SKNN) method. When choosing the nearest neighbors of missing observations, the proposed SANN method takes the local feature of the missing observations into account as well as reutilizes the imputed observations in a sequential manner. By using a Monte Carlo study and a real data example, we demonstrate the characteristics of the SANN method and its potential performance.

• Journal of Distribution Research
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• v.10 no.3
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• pp.87-101
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• 2005

Market segmentation has been an important issue in marketing for a long time. Many models and statistical methods have been developed by many scholars. The purpose of this research provides one insight for market segmentation based on clustering technique in channel benefit sought. We proposed a sequential approach in market segmentation. A sequential approach means that we do market segmentation by multi-stage method based on the benefits sought in marketing channel. To achieve this approach, we divided the main benefits sought into subcategories. That is to say, after dividing each benefit sought into more detailed concepts, we did market segmentation sequentially.

• Journal of the Korea Computer Industry Society
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• v.2 no.4
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• pp.507-520
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• 2001

In this paper, a hybrid algorithm for well detecting both abrupt and gradual scene changes is proposed. This algorithm examines only the candidate intervals for speedup using the binary tree method and skips the intervals that are not candidate. For accuracy, the temporal difference of variance is used to detect the gradual scene changes while the temporal difference of histogram is used to detect the abrupt scene changes. Experimental results show that the proposed hybrid algorithm using the binary tree method works up about 10 times faster that the sequential method and is effective in detecting abrupt scene change and gradual transitions including dissolving and fading.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.75-82
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• 2009

In this paper, we propose a robust preprocessing scheme for entropy coding in gray-level image. The issue of this paper is to reduce additional information needed when bit stream is transmitted. The proposed scheme uses the preprocessing method of co-occurrence count about gray-levels in neighboring pixels. That is, gray-levels are substituted by their ranked numbers without additional information. From the results of computer simulation, it is verified that the proposed scheme could be reduced the compression bit rate by up to 44.1%, 37.5% comparing to the entropy coding and conventional preprocessing scheme respectively. So our scheme can be successfully applied to the application areas that require of losslessness and data compaction.