• Journal of KIISE
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• v.43 no.5
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• pp.509-515
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• 2016

Given a text T and a pattern P, the order-preserving pattern matching problem is to find all substrings in T which have the same relative orders as P. The order-preserving pattern matching problem has been studied in terms of finding some patterns affected by relative orders, not by their absolute values. Given a text T and a pattern set $\mathbb{P}$, the order-preserving multiple pattern matching problem is to find all substrings in T which have the same relative orders as any pattern in $\mathbb{P}$. In this paper, we present a hashing-based algorithm for the order-preserving multiple pattern matching problem.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.548-554
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• 2009

We propose an automatic inspection system for hologram with multiple patterns. The system hardware consists of illuminations, camera, and vision processor. Multiple illuminations using LEDs are arranged in different directions to acquire each image of patterns. The system software consists of pre-processing, pattern generation, and pattern matching. The acquired images of input hologram are compared with their reference patterns by developed matching algorithm. To compensate for the positioning error of input hologram, reference patterns of hologram for different position should be generated in on-line. We apply a frequency transformation based CGH(computer-generated hologram) method to generate reference images. For the fast pattern matching, we also apply the matching method in the frequency domain. Experimental results for hologram of Korean currency are then presented to verify the usefulness of proposed system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.27-37
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• 2011

The IDS/IPS(Intrusion Detection/Prevention System) has been widely deployed to protect the internal network against internet attacks. Reducing the packet inspection time is one of the most important challenges of improving the performance of the IDS/IPS. Since the IDS/IPS needs to match multiple patterns for the incoming traffic, we may have to apply the multiple pattern matching schemes, some of which use finite automata, while the others use the shift table. In this paper, we first show that the performance of those schemes would degrade with various kinds of pattern sets and payload, and then propose a hybrid multiple pattern matching scheme which combines those two schemes. The proposed scheme is organized to guarantee an appropriate level of performance in any cases. The experimental results using real traffic show that the time required to do multiple pattern matching could be reduced effectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.3
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• pp.79-88
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• 2008

On the internet, the NIDS(Network Intrusion Detection System) has been widely deployed to protect the internal network. The NIDS builds a set of rules with analysis results on illegal packets and filters them using the rules, thus protecting the internal system. The number of rules is ever increasing as the attacks are becoming more widespread and well organized these days. As a result, the performance degradation has been found severe in the rule application fer the NIDS. In this paper, we propose a multiple pattern matching scheme to improve rule application performance. Then we compare our algorithm with Wu-Mantel algorithm which is known to do high performance multi-pattern matching.

• The KIPS Transactions:PartA
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• v.12A no.2 s.92
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• pp.87-94
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• 2005

Pattern matching is one of critical parts of Network Intrusion Prevention Systems (NIPS) and computationally intensive. To handle a large number of attack signature fattens increasing everyday, a network intrusion prevention system requires a multi pattern matching method that can meet the line speed of packet transfer. In this paper, we analyze Snort, a widely used open source network intrusion prevention/detection system, and its pattern matching characteristics. A multi pattern matching method for NIPS should efficiently handle a large number of patterns with a wide range of pattern lengths and case insensitive patterns matches. It should also be able to process multiple input characters in parallel. We propose a multi pattern matching hardware accelerator based on Shift-OR pattern matching algorithm. We evaluate the performance of the pattern matching accelerator under various assumptions. The performance evaluation shows that the pattern matching accelerator can be more than 80 times faster than the fastest software multi-pattern matching method used in Snort.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.142-151
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• 1993

An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.

• Annual Conference of KIPS
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• 2005.05a
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• pp.521-524
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• 2005

This paper proposes a fusion algorithm which merges multiple vein pattern images into a single image, larger than those images. As a preprocessing step of template matching, during the verification of biometric data such as fingerprint image, vein pattern image of hand, etc., the fusion technique is used to make reference image larger than the candidate images in order to enhance the matching performance. In this paper, a new algorithm, called BSA (Boundary Stitching Algorithm) is proposed, in which the boundary rectilinear parts extracted from the candidate images are stitched to the reference image in order to enlarge its matching space. By applying BSA to practical vein pattern verification system, its verification rate was increased by about 10%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.395-404
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• 2013

A pattern matching algorithm plays an important role in traffic identification and classification based on predefined patterns for intrusion detection and prevention. As attacks become prevalent and complex, current patterns are written using regular expressions, called regexes, which are expressed into the deterministic finite automata(DFA) due to the guaranteed worst-case performance in pattern matching process. Currently, because of the increased complexity of regex patterns and their large number, memory-efficient DFA from states reduction have become the mainstay of pattern matching process. However, most of the previous works have focused on reducing only the number of states on a single automaton, and thus there still exists a state blowup problem under the large number of patterns. To solve the above problem, we propose a new state compression algorithm that merges states on multiple automata. We show that by merging states with the same input character on multiple automata, the proposed algorithm can lead to a significant reduction of the number of states in the original DFA by as much as 40.0% on average.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.503-510
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• 2005

With the increasing importance of network protection from cyber threats, it is requested to develop a multi-gigabit rate pattern matching method for protecting against malicious attacks in high-speed network. This paper devises a high-speed pattern matching algorithm with TCAM by using an m-byte jumping window pattern matching scheme. The proposed algorithm significantly reduces the number of TCAM lookups per payload by m times with the marginally enlarged TCAM size which can be implemented by cascading multiple TCAMs. Due to the reduced number of TCAM lookups, we can easily achieve multi-gigabit rate for scanning the packet payload. It is shown by simulation that for the Snort nile with 2,247 patterns, our proposed algorithm supports more than 10 Gbps rate with a 9Mbit TCAM.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.23-30
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• 2014

Feature matching using image descriptors is robust method used recently. However, mismatches occur in 3D transformed images, illumination-changed images and repetitive-pattern images. In this paper, we observe that there are a lot of mismatches in the images which have repetitive patterns. We analyze it and propose a method to eliminate these mismatches. MDMF(Multiple Descriptors-based Mismatch Filtering) eliminates mismatches by using descriptors of nearest several features of one specific feature point. In experiments, for geometrical transformation like scale, rotation, affine, we compare the match ratio among SIFT, ASIFT and MDMF, and we show that MDMF can eliminate mismatches successfully.