• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.27-33
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• 2020

Backward compatibility is one of the key issues for radio equipment supporting IEEE 802.11, the typical wireless local area networks (WLANs) communication protocol. For a successful packet decoding with the backward compatibility, the frame format detection is a core precondition. This paper presents a novel frame format detection method based on a deep learning procedure for WLANs affiliated with IEEE 802.11. Considering that the detection performance of conventional methods is degraded mainly due to the poor performances in the symbol synchronization and/or channel estimation in low signal-to-noise-ratio environments, we propose a novel detection method based on convolutional neural network (CNN) that replaces the entire conventional detection procedures. The proposed deep learning network provides a robust detection directly from the receive data. Through extensive computer simulations performed in the multipath fading channel environments (modeled by Project IEEE 802.11 Task Group ac), the proposed method exhibits superb improvement in the frame format detection compared to the conventional method.

• Journal of Fisheries and Marine Sciences Education
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• v.17 no.2
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• pp.270-280
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• 2005

Many researchers have proposed the various methods to detect illegal intrusion in order to improve internet environment. Among these researches, IDS(Intrusion Detection System) is classified the most common model to protect network security. In this paper, we propose new log format instead of Apache log format for SSL integrity verification. We translate file-DB log format into R-DB log format. Using these methods we can manage Web server's integrity, and log data is transmitted verification system to be able to perform both primary function of IDS and Web server's integrity management at the same time. The proposed system in this paper is also able to use for wire and wireless environment based on PDA.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.65-71
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• 2013

In this work, new smart phone based moving target detection is proposed. In order to implement the task, methods of real time image transmission from network camera, motion detecting algorithm and its effective implementation are also addressed. The network camera transfers image data by MJPEG format which contains various information such as data and IP address, and the smart phone separates the image data received through a WiFi module. Later, the image data is converted to a Bitmap image format, and with the help of the embedded OpenCV library on a smart phone and algorithm, it was found that the moving object was identified effectively in terms of real time monitoring and detection.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.67-78
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• 2020

Typical security solutions such as intrusion detection system are not suitable for detecting advanced persistent attack(APT), because they cannot draw the big picture from trivial events of security solutions. Researches on techniques for detecting multiple stage attacks by analyzing the correlations between security events or alerts are being actively conducted in academic field. However, these studies still use events from existing security system, and there is insufficient research on the structure of the entire security system suitable for advanced persistent attacks. In this paper, we propose an attack path and intention recognition system suitable for multiple stage attacks like advanced persistent attack detection. The proposed system defines the trace format and overall structure of the system that detects APT attacks based on the correlation and behavior analysis, and is designed with a structure of detection system using deep learning and big data technology, etc.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2001.11a
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• pp.381-384
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• 2001

개개의 침입탐지 시스템에서 탐지한 경보(alert) 자료의 공유를 쉽게 하기 위해서, IETF(Internet Engineering Task Force)에서는 IDEF(Intrusion Detection Exchange Format)모델을 제안하였다[1]. 특히, IDEF는 최근에 관심이 모아지고 있는 다수의 침입탐지 시스템(이하 ‘통합 침입탐지 시스템’)을 통합 관리하는 방식에서 각 단말 침입 탐지시스템의 침입 경보자료의 수집 관리를 용이하게 할 수 있다. 그러나, 통합 침입탐지 시스템에서 개개의 침입 탐지 시스템에서 발견하지 못하는 침입을 판단하거나 판단의 정확성을 높이기 위해서는 기존의 IDEF에 추가적인 자료가 요구되어 진다. 본 논문에서는 통합 침입탐지 시스템의 상위 시스템에서 수집된 경보 자료를 IDEF의 관계형 데이터베이스 스키마로 변환하는 방식을 제시하였다. 그리고, 통합 침입탐지시스템에서 추가적으로 필요한 자료에 의거하여 DDoS공격탐지에 필요한 자료형을 IDEF에 확장하였다.

• BMB Reports
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• v.31 no.1
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• pp.101-105
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• 1998

Immunoassay of botulinum toxin (BTX) B type was investigated using two typed of biosensors: light addressable potentiometric sensor (LAPS) and surface plasmon resonance (SPR) sensor. Urease-tagged and immuno-filtration capture method have been used for LAPS. Tag-free and direct binding real-time detection method have been used for SPR sensor. The detection limit of sandwich assay format with LAPS was 10 ng/ml, which was the lowest among methods tested. SPR has the advantage of being more convenient because tag-free direct binding assay can be used and reaction time was reduced, regardless of low sensitivity. This result shows that sandwich assay format with LAPS can be used as an alternative method of BTX mouse bioassay which is known as the most sensitive method for the detection of BTX.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.4
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• pp.29-37
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• 2010

The change detection of XML documents is a major research area. However, though XML becomes a file format for Hangul documents, research on change detection of Hangul documents based on the characteristics of Hangul documents is rather scarce. Since format data in Hangul documents are very large, which is different from ordinary XML documents, it is not proper to apply general XML change detection algorithms such as X-treeDiff+ to Hangul documents without any change. In this paper, we propose new contents-based matching algorithm and implement it in X-treeDiff+. The result of our testing shows better performance for most documents in editing process.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.87-93
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• 2022

Since 99% of PCs operating in the defense domain use the Windows operating system, detection and response of Window-based malware is very important to keep the defense cyberspace safe. This paper proposes a model capable of detecting malware in a Windows PE (Portable Executable) format. The detection model was designed with an emphasis on rapid update of the training model to efficiently cope with rapidly increasing malware rather than the detection accuracy. Therefore, in order to improve the training speed, the detection model was designed based on a Bidirectional LSTM (Long Short Term Memory) network that can detect malware with minimal sequence data without complicated pre-processing. The experiment was conducted using the EMBER2018 dataset, As a result of training the model with feature sets consisting of three type of sequence data(Byte-Entropy Histogram, Byte Histogram, and String Distribution), accuracy of 90.79% was achieved. Meanwhile, it was confirmed that the training time was shortened to 1/4 compared to the existing detection model, enabling rapid update of the detection model to respond to new types of malware on the surge.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.124-130
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• 2008

We present in this paper a method of digital watermarking for video data based on the discrete wavelet transform. In the proposed method, a watermark signal is inserted into the decompressed bitstream while detection is performed using the uncompressed video. This method allows detection if video has been manipulated or its format changed. We embed the watermark in the lowest frequency components of each frame in the un-coded video by using wavelet transform. The watermark can be extracted directly from the decoded video without access to the original video. Experimental results show that the proposed method gives the watermarked video of better quality and is robust against MPEG coding, down sampling and re-encoding to other type of video format such as MPEG4, H.264

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.334-342
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• 2007

This paper presents an algorithm for the automatic detection of chord names, scales and tonalities from music file, expressed in MusicXML format which has enough information to determine harmonies vertically like 4-part choir. Chord names are absolute names which can be used and analysed independently of the tonality An algorithm selecting the best chord name is described, which can decide the most appropriate one from ambiguous situations. Candidate musical scales are extracted using the notes in a given time window. The tonalities of the music are determined using the chord names and candidate scales. The final output format of the process is also MusicXML file with chord names, marked non-harmonic notes, relative harmonic symbols and tonalities.