• Review of KIISC
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• 제27권6호
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• pp.29-32
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• 2017

현대 사회에서 주요 사회적 이슈가 되는 CCTV, 네트워크 프린터, 스마트 가전기기 등 IoT 장비 해킹 사고의 발생 횟수 및 피해 규모는 지속적으로 증가하고 있다. 최근 침해사고 사례를 살펴보면, 엔드포인트에 해당하는 IoT 장비의 허술한 보안대책으로 인하여 악성코드 설치 및 실행을 탐지하지 못한 피해가 대부분이다. 이로 인해 IoT 장비에 대한 악성 프로세스 실행 제어 제품이 개발되어 도입되는 추세이지만, 아직까지 안전성 평가에 대한 연구가 부족한 실정이다. 따라서 본 논문에서는 IoT 장비에 대한 악성 프로세스 실행 제어 제품의 기본 보안요구사항을 식별하고, 필요한 시험항목과 시험 시 유의사항에 대해 제안한다.

• Review of KIISC
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• 제32권5호
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• pp.45-51
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• 2022

소프트웨어의 개발에서 오픈소스 소프트웨어(Open Source Software, 이하 OSS)의 사용이 급증하고있다. 이애에 많은 OSS의 재사용 및 OSS간 재사용으로 인하여 OSS의 신규 취약점 대응 및 관리가 어려워지고 있다. 따라서 본 논문에서는 인공지능을 이용하여 OSS 프로젝트의 구조적 정보를 활용하여 여러 가지 OSS 재사용 기법에 대응하는 개선된 OSS 재사용 탐지(OSS Cloning Detection, OCD) 기술을 제안하고 그 성능을 평가한다.

• The Journal of the Korea institute of electronic communication sciences
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• 제18권6호
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• pp.1217-1228
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• 2023

In this paper, technical and patent analysses of anti-drone technology, which aim to neutralize drone attacks are conducted. We conducted research on the technical definition of anti-drone, the technical elements of anti-drone systems, and investigated the patents related to anti-drone and drone filed domestically and internationally over the past 10 years, starting from 2011. For domestic patents, we examined the number of patent applications related to anti-drone and the overall domestic patent applications over the past 10 years. Regarding international filings, we investigated the patent applications related to anti-drone filed in the United States, Europe, Japan, China, and under the PCT system in the past 10 years. We conducted a search for patents related to anti-drone, including neutralization techniques identified under the keyword "anti-drone," patents related to drone detection and identification techniques, and patents related to drone neutralization techniques. Through the conducted research, a total of 91 patents were filed for drone detection techniques. Out of these, 5 patents, accounting for 5.5%, were filed by public institutions. In the case of patents filed for drone identification techniques, there were a total of 174 patents. Among these, 4 patents, which is 2.3%, were filed by public institutions.

• Proceedings of the Korean Society of Computer Information Conference
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.1-2
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• 2018

해상 선박의 안전을 위해 해저의 객체 및 장애물의 정확한 탐지를 위해 해저환경에서 감쇠현상이 비교적 적은 음파 기반의 소나가 널리 활용된다. 그러나 기존의 소나 영상 시뮬레이션은 고해상도의 영상, 잡음 처리, 해저지형과 객체 데이터 등의 방대한 데이터 처리로 인해 물체 탐지 및 식별을 위한 처리속도와 비용이 크게 증가한다. 이러한 문제를 최소화하기 위해서 해저지형, 객체 생성과 잡음 처리 모델을 Multi-Threading, SIMD 등 병렬처리를 적용하여 처리속도를 최적화 한다. 본 논문에서는 혼합된 병렬처리 방법을 적용하여 소나를 기반으로 해저 환경 시뮬레이션을 위한 모의 신호를 생성하는 성능을 향상시킨다. 병렬처리로 인해 개선된 성능을 순차처리에 따른 속도와 실험적으로 비교한다.

• Annual Conference of KIPS
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• 한국정보처리학회 2003년도 춘계학술발표논문집 (하)
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• pp.1555-1558
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• 2003

침입탐지란 컴퓨터와 네트워크 자원에 대한 유해한 침입 행동을 식별하고 대응하는 과정이다. 점차적으로 시스템에 대한 침입의 유형들이 복잡해지고 전문적으로 이루어지면서 빠르고 정확한 대응을 필요로 하는 시스템이 요구되고 있다. 이에 대용량의 데이터를 분석하여 의미 있는 정보를 추출하는 데이터 마이닝 기법을 적용하여 지능적이고 자동화된 탐지 및 경보데이터 분석에 이용할 수 있다. 마이닝 기법중의 하나인 순차 패턴 탐사 방법은 일정한 시퀸스 내의 빈발한 항목을 추출하여 순차적으로 패턴을 탐사하는 방법이며 이를 이용하여 시퀸스의 행동을 예측하거나 기술할 수 있는 규칙들을 생성할 수 있다. 이 논문에서는 대량의 경보 데이터를 효율적으로 분석하고 반복적인 공격 패턴에 능동적인 대응을 위한 방법으로 확장된 순차패턴 알고리즘인 PrefixSpan 알고리즘에 대해 제안하였고 이를 적용하므로써 침입탐지 시스템의 자동화 및 성능의 향상을 얻을 수 있다.

• Journal of Intelligence and Information Systems
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• 제18권2호
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2017년도 추계학술대회
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• pp.699-701
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• 2017

Typical operating method for long-range observation cameras are to detect the target at a wide angle of view and to recognize/identify the target with a telephoto angle of view. And the detection/recognition range performance is an important item to evaluate the performance of the defense infrared camera. To increased the detection range performance, the camera's field of view should be narrowed. Due to the narrow field of view, the probability of finding target is relatively low. In this paper, we propose a method to search for target by providing a wide angle view while maintaining detection range performance. M&S and optimized design were used to develop infrared camera with extended field of view and the results of the test summarized.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제25권3호
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• pp.449-455
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• 2021

This paper proposes an encryption web transaction attack detection system based on the existing web application monitoring system. Although there was difficulty in detecting attacks on the encrypted web traffic because the existing web traffic security systems detect and defend attacks based on encrypted packets in the network area of the encryption section between the client and server, by utilizing the technology of the web application monitoring system, it is possible to detect various intelligent cyber-attacks based on information that is already decrypted in the memory of the web application server. In addition, since user identification is possible through the application session ID, statistical detection of attacks such as IP tampering attacks, mass web transaction call users, and DDoS attacks are also possible. Thus, it can be considered that it is possible to respond to various intelligent cyber attacks hidden in the encrypted traffic by collecting and detecting information in the non-encrypted section of the encrypted web traffic.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제21권1호
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• pp.61-68
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• 2021

In the past, radars have been classified into fire control radars, detection radars, tracking radars, and image acquisition radars according to the characteristics of the mission. However, multi-function radars perform various tasks within a single system, such as target detection, tracking, identification friend or foe, jammer detection and response. Therefore, efficient resource management is essential to operate multi-function radars with limited resources. In particular, the target threat for tracking the detected target and the method of selecting the tracking cycle based on this is an important issue. If focus on tracking a threat target, Radar can't efficiently manage the targets detected in other areas, and if you focus on detection, tracking performance may decrease. Therefore, effective scheduling is essential. In this paper, we propose the TaP (Time and Priority) algorithm, which is a multi-functional radar scheduling scheme, and a software design method to construct it.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제34권4호
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• pp.615-627
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• 2024

With the evolution of power systems and advancements in IT technology, there is an increasing demand to shift from serial-based communication to TCP/IP-based communication. However, TCP/IP communication entails various security threats, necessitating extensive consideration from an information security perspective. Security measures such as authentication and encryption cannot be rapidly implemented due to issues like the replacement of Remote Terminal Units (RTUs) and the performance requirements of encryption algorithms. This paper proposes a state estimation-based intrusion detection model to identify and effectively detect threats to power control systems in such a context. The proposed model, in addition to signature detection methods, verifies the validity of acquired data, enabling it to detect attacks that are difficult to identify using traditional methods, such as data tampering.