• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.488-493
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• 1989

In this paper, the structure of CMAC address mapping is first revisited, and the address hashing function and the random mapping is discussed in the conventional CMAC implementation. Then the effective size of CMAC memory is derived from the modulus property of the CMAC address vector, and a new hashing function for the effective memory mapping is proposed for a CMAC implementation with feasible memory size and no troublesome random mapping. Finally, the performance of the conventional CMAC learning algorithm and that of the proposed new CMAC scheme arc compared via simulations.

• Journal of Computing Science and Engineering
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• v.11 no.1
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• pp.1-8
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• 2017

Naive Bayes nearest neighbor (NBNN) is a simple image classifier based on identifying nearest neighbors. NBNN uses original image descriptors (e.g., SIFTs) without vector quantization for preserving the discriminative power of descriptors and has a powerful generalization characteristic. However, it has a distinct disadvantage. Its memory requirement can be prohibitively high while processing a large amount of data. To deal with this problem, we apply a spherical hashing binary code embedding technique, to compactly encode data without significantly losing classification accuracy. We also propose using an inverted index to identify nearest neighbors among binarized image descriptors. To demonstrate the benefits of our method, we apply our method to two existing NBNN techniques with an image dataset. By using 64 bit length, we are able to reduce memory 16 times with higher runtime performance and no significant loss of classification accuracy. This result is achieved by our compact encoding scheme for image descriptors without losing much information from original image descriptors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.11C
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• pp.1040-1045
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• 2002

This paper focuses on a hash-based, distributed Wet caching network that eliminates inter-cache communication. An agent program on cache servers, a mapping program on the DNS server, and other components comprised in a distributed Web caching network were modified and developed to implement a so-called "consistent" hashing. Also, a dynamic load balancing algorithm is proposed to address the load-balancing problem that is a key performance issue on distributed architectures. This algorithm effectively balances the load among cache servers by distributing the calculated amount of mapping items that have higher popularity than others. Therefore, this developed network can resolve the imbalanced load that is caused by a variable page popularity, a non-uniform distribution of a hash-based mapping, and a variation of cache servers.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.1
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• pp.75-82
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• 2003

Computer and network security has recently become a popular subject due to the explosive growth of the Internet Especially, attacks based on malformed packet are difficult to detect because these attacks use the skill of bypassing the intrusion detection system and Firewall. This paper designs and implements a network-based intrusion detection system (NIDS) which detects intrusions with malformed-packets in real-time. First, signatures, rules in NIDS like Snouts rule files, are classified using similar properties between signatures NIDS creates a rule tree applying hashing technique based on the classification. As a result the system can efficiently perform intrusion detection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1047-1054
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• 2004

One of the fundamental problems in computer science is how to store information so that it can be searched and retrieved efficiently. Hashing is a technique which solves this problem. In this paper, we propose a tree construction algorithm using linear two-predecessor single attractor cellular automata C and its complemented cellular automata. Also by using the concept of MRT we give a perfect hasing algorithm based on C.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.76-82
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• 2017

An image hash, a discriminative and robust summary of an image, should be robust against quality-preserving signal processing steps, while being pairwise independent for perceptually different inputs. In order to improve the hash matching performance, this paper proposes a probabilistic dissimilarity matching. Instead of extracting the binary hash from the query image, we compute the probability that the intermediate hash vector of the query image belongs to each quantization bin, which is referred to as soft quantization binning. The probability is used as a weight in comparing the binary hash of the query with that stored in a database. A performance evaluation over sets of image distortions shows that the proposed probabilistic matching method effectively improves the hash matching performance as compared with the conventional Hamming distance.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.180-182
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• 2012

플래시 메모리는 고성능, 저전력 등 많은 장점을 가지고 있어 PC를 비롯한 각종 단말에서 아주 많이 사용되고 있다. 하지만 기존의 시스템들은 디스크 기반 저장 장치의 특성을 고려하여 설계되었기 때문에 플래시 메모리 저장 장치에 맞게 수정한다면 더욱 좋은 성능을 기대할 수 있다. 본 논문에서는 그 중에서도 파일 시스템 및 데이터베이스에서 많이 쓰이고 있는 해시 인덱스 기법을 플래시 메모리 저장 장치에 특성에 맞춘 원형 해시 인덱스 기법을 제안한다. 원형 해시 인덱스 기법은 New Dynamic Hashing 기법의 단점을 보완하여 보다 나은 성능을 제공한다.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.270-272
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• 1999

최근에 활발히 연구되고 있는 지리 정보 시스템 등은 2차원 이상의 공간 속성을 갖는 공간 객체들로 구성되며 데이터 양이 매우 방대하여 효율적인 공간 색인 기법이 요구되고 있다. 그러나, 기존의 공간 색인 기법들은 공간 객체의 크기와 밀도 차이, 공간 연산의 종류에 따라 각각 큰 성능차를 보이며 때로는 이용이 불가능한 경우도 있다. 이와 같은 문제점들을 해결하기 위해서는 공간 객체의 크기와 밀도 차이에 독립적인 하나의 색인 구조로 다양한 공간 연산들을 효율적으로 지원할 수 있는 공간 색인 기법이 필요하다. 본 논문에서는 이와 같은 문제를 해결할 수 있는 새로운 공간 색인 기법인 공간 해싱(spatial hashing)을 제안하고 관련연산들을 정의하였다. 공간 해싱은 각 객체의 영역을 MBR로 단순화하고 그 MBR의 좌상점(Left-Top point)와 우하점(Right-Bottom point) 만을 이용해 객체의 영역 정보와 위치 정보를 확장성 해싱을 이용하여 유지하는 색인 기법이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.776-779
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• 2015

컴퓨터의 연산 속도와 공격자의 기법 등이 발달함에 따라 사용자들의 패스워드들을 더욱 안전하게 보관될 필요성이 증가하였다. 이에 따라, 새로운 패스워드 보호 기술을 개발하기 위한 PHC(password hashing competition) 공모전이 개최되었다. 본 연구에서는 공모전을 통해 해싱 알고리즘들이 추구하는 암호학적 특징들을 분석하고, 패스워드 해싱 기술의 향후 발전 동향을 예측하고자 한다.

• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.145-156
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• 2000

Clustering is the process of partitioning a data set into meaningful clusters. As the data to process increase, a laster algorithm is required than ever. In this paper, we propose a clustering algorithm to partition a multispectral remotely sensed image data set into several clusters using a hash search algorithm. The processing time of our algorithm is compared with that of clusters algorithm using other speed-up concepts. The experiment results are compared with respect to the number of bands, the number of clusters and the size of data. It is also showed that the processing time of our algorithm is shorter than that of cluster algorithms using other speed-up concepts when the size of data is relatively large.