• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1486-1492
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• 2007

Searching distributed resources efficiently is very important in distributed computing environments like P2P. But distributed resource searching may have system overheads and take a lot of time in proportion to the searching number, because distributed resource searching has to circuit many peers for searching information. In this paper, we design a proxy peer algorithm based on DHT(Distributed Hash Table) for efficient distributed resource searching in JXTA network environments. By containing the rendezvous information in proxy peer and searching a rendezvous peer firstly which has higher hit ratio, we can reduce the searching number and minimize system overheads.

• Convergence Security Journal
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• v.9 no.4
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• pp.21-27
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• 2009

In the environment of development of network bandwidth and intrusion technology there is limit to the pattern analysis of all massed packets through the existing pattern matching method by the intrusion detection system. To detect the packets efficiently when they are received fragmented, it has been presented the matching method only the pattern of packets consisting with the operation system such as Esnort. Pattern matching performance is improved through the use of NMAP, the basic mechanism od Esnort, by scanning the operation system of the same network system and appling pattern match selectively scanned information and the same operation system as the received packets. However, it can be appeared the case of disregarding the receivied packets depending on the diversity of the kind of operation systems and recognition mistake of operation system of nmap. In this paper, we present and verify the improved intrusion detection system shortening the pattern matching time by the creation of hashy table through the pattern hash of intrusion detection system independently with the users system environment .in the state of flux.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.179-188
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• 2005

Much research for spatial join has been extensively studied over the last decade. In this paper, we focus on the filtering step of candidate objects for spatial join operations on the input tables that none of the inputs is indexed. In this case, many algorithms has presented and showed excellent performance over most spatial data. However, if data sets of input table for the spatial join ale skewed, the join performance is dramatically degraded. Also, little research on solving the problem in the presence of skewed data has been attempted. Therefore, we propose a spatial hash strip join (SHSJ) algorithm that combines properties of the existing spatial hash join (SHJ) algorithm based on spatial partition for input data set's distribution and SSSJ algorithm. Finally, in order to show SHSJ the outperform in uniform/skew cases, we experiment SHSJ using the Tiger/line data sets and compare it with the SHJ algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.1
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• pp.11-21
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• 2008

Biometrics-based user authentication has several advantages over traditional password-based systems for standalone authentication applications. This is also true for new authentication architectures known as crypto-biometric systems, where cryptography and biometrics are merged to achieve high security and user convenience at the same time. Recently, a cryptographic construct, called fuzzy vault, has been proposed for crypto-biometric systems. This construct aims to secure critical data(e.g., secret key) with the fingerprint data in a way that only the authorized user can access the secret by providing the valid fingerprint, and some implementations results for fingerprint have been reported. However, the previous results had some limitation of the provided security due to the limited numbers of chaff data fer hiding real fingerprint data. In this paper, we propose an approach to provide both the automatic alignment of fingerprint data and higher security by using a 3D geometric hash table. Based on the experimental results, we confirm that the proposed approach of using the 3D geometric hash table with the idea of the fuzzy vault can perform the fingerprint verification securely even with more chaff data included.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2061-2068
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• 2016

A Bloom filter is a space-efficient data structure popularly applied in many network algorithms. This paper proposes a vectored Bloom filter to provide a high-speed Internet protocol (IP) address lookup. While each hash index for a Bloom filter indicates one bit, which is used to identify the membership of the input, each index of the proposed vectored Bloom filter indicates a vector which is used to represent the membership and the output port for the input. Hence the proposed Bloom filter can complete the IP address lookup without accessing an off-chip hash table for most cases. Simulation results show that with a reasonable sized Bloom filter that can be stored using an on-chip memory, an IP address lookup can be performed with less than 0.0003 off-chip accesses on average in our proposed architecture.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.752-760
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• 2009

Emerging peer-to-peer systems benefit from the large amount of resources provided by many peers. However, many peer-to-peer systems or applications suffer from malicious peers and it is not guaranteed that peers are always online. Micropayment systems are accounting and charging mechanism for buying services, so we can apply them to solve these problems. In the past the majority of micropayment system uses a centralized broker but the problem with most existing micropayment system is a heavy load on the broker. For instance, when an owner of the coin is offline, the broker delegates the owner and handles payment messages. It occurs frequently because of characteristic of peer-to-peer system and is another load of the broker. In this paper we introduce DPay, a peer-to-peer micropayment system that uses distributed hash table (DHT) for storing encrypted payment messages and increases scalability and reduces the load of broker by removing downtime protocol. We show the idea of real-time double spending detection in DPay and report the results of several evaluations in order to compare DPay and other payment scheme. In simulation result, the load of broker in DPay is reduced by 30% on average of other previous payment scheme. We expect that DPay can apply various peer-to-peer systems because it provides a real-time double spending detection and stores more secure payment messages.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.228-238
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• 2018

With the rapid advancement of Internet services, there has been a dramatic increase in services that dynamically provide Internet resources on demand, such as cloud computing. In a cloud computing service, because the number of users in the cloud is changing dynamically, it is more efficient to utilize a flexible network technology such as software-defined networking (SDN). However, to efficiently support the SDN-based cloud computing service with limited resources, it is important to effectively manage the flow table at the SDN switch. Therefore, in this paper, a new flow management scheme is proposed that is able to, through efficient management, speed up the flow-entry search speed and simultaneously maximize the number of flow entries. The proposed scheme maximizes the capacity of the flow table by efficiently storing flow entry information while quickly executing the operation of flow-entry search by employing a hash index. In this paper, the proposed scheme is implemented by modifying the actual software SDN switch and then, its performance is analyzed. The results of the analysis show that the proposed scheme, by managing the flow tables efficiently, can support more flow entries.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.6
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• pp.127-138
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• 2019

The data response speed is a critical issue of cloud services because it directly related to the user experience. As such, the in-memory database is widely adopted in many cloud-based applications for achieving fast data response. However, the current implementation of the in-memory database is mostly based on the linked list-based hash table which cannot guarantee the constant data response time. Thus, cuckoo hashing was introduced as an alternative solution, however, there is a disadvantage that only half of the allocated memory can be used for storing data. Subsequently, bucketized cuckoo hashing (BCH) improved the performance of cuckoo hashing in terms of memory efficiency but still cannot overcome the limitation that the insert overhead. In this paper, we propose a data management solution called Wall Cuckoo which aims to improve not only the insert performance but also lookup performance of BCH. The key idea of Wall Cuckoo is that separates the data among a bucket according to the different hash function be used. By doing so, the searching range among the bucket is narrowed down, thereby the amount of slot accesses required for the data lookup can be reduced. At the same time, the insert performance will be improved because the insert is following up the operation of the lookup. According to analysis, the expected value of slot access required for our Wall Cuckoo is less than that of BCH. We conducted experiments to show that Wall Cuckoo outperforms the BCH and Sorting Cuckoo in terms of the amount of slot access in lookup and insert operations and in different load factor (i.e., 10%-95%).

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.46-48
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• 2004

Distributed Hash Table(DHT)를 기반으로 하는 structured P2P에서 복잡 질의를 통친 원하는 자료를 찾는 것은 쉽지 않다. 이와 같은 것들 중 하나가 범위 값을 이용하여 원하는 값을 찾는 range query이다. 본 논문에서는 full binary tree의 특징을 이용하여 structured P2P에서 range query를 수행할 수 있는 mapping 함수와, load balance를 지원하기 위한 방법을 제안한다 또한 실험을 통해서 이 방법들이 어느 정도의 성능을 보여주는 지도 살펴본다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2105-2112
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• 2009

Recently RFID system has been adopted in various fields rapidly. However, we ought to solve the problem of privacy invasion that can be occurred by obtaining information of RFID Tag without any permission for popularization of RFID system To solve the problems, it is Ohkubo et al.'s Hash-Chain Scheme which is the safest method. However, this method has a problem that requesting lots of computing process because of increasing numbers of Tag. Therefore, We suggest the way (process) satisfied with all necessary security of Privacy Protection Shreme and decreased in Tag Identification Time in this paper. First, We'll suggest the SP-Division Algorithm seperating SPs using the Performance Measurement consequence of each node after framing the program to create Hash-Chain Calculated table to get optimized performance because of character of the grid environment comprised of heterogeneous system. If we compare consequence fixed the number of nodes to 4 with a single node, equal partition, and SP partition, when the total number of SPs is 1000, 40%, 49%, when the total number of SPs is 2000, 42%, 51%, when the total number of SPs is 3000, 39%, 49%, and when the total number of SPs is 4000, 46%, 56% is improved.