• Title/Summary/Keyword: signature-based detection

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Analysis of Flow and Infrared Signature Characteristics according to UCAV Nozzle Shape (무인전투기 배기구 형상에 따른 유동 및 적외선 신호 특성 분석)

  • Noh, Sooyoung;Bae, Ji-Yeul;Kim, Jihyuk;Nam, Juyeong;Jo, Hana;Cho, Hyung Hee
    • Journal of the Korean Society of Propulsion Engineers
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    • v.23 no.5
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    • pp.27-35
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    • 2019
  • Stealth technology is a technique to avoid detection from detectors such as radar and infrared seekers. In particular, detection by infrared signature is more threatening because infrared missiles detect heat from the aircraft itself. Therefore, infrared stealth technology is essential for ensuring the survival of aircraft and unmanned combat aerial vehicles (UCAV). In this study, we analyzed aerodynamic and infrared stealth performance in relation to UCAV nozzle design. Based on simulation results, a double serpentine nozzle was effective in reducing the infrared signature because it could shield high-temperature components in the engine. In addition, we observed that the infrared signature was reduced at the turning position of the duct located at the rear part of the double serpentine nozzle.

Virus Detection Method based on Behavior Resource Tree

  • Zou, Mengsong;Han, Lansheng;Liu, Ming;Liu, Qiwen
    • Journal of Information Processing Systems
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    • v.7 no.1
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    • pp.173-186
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    • 2011
  • Due to the disadvantages of signature-based computer virus detection techniques, behavior-based detection methods have developed rapidly in recent years. However, current popular behavior-based detection methods only take API call sequences as program behavior features and the difference between API calls in the detection is not taken into consideration. This paper divides virus behaviors into separate function modules by introducing DLLs into detection. APIs in different modules have different importance. DLLs and APIs are both considered program calling resources. Based on the calling relationships between DLLs and APIs, program calling resources can be pictured as a tree named program behavior resource tree. Important block structures are selected from the tree as program behavior features. Finally, a virus detection model based on behavior the resource tree is proposed and verified by experiment which provides a helpful reference to virus detection.

A Study on Signature-based Wireless Intrusion Detection Systems (시그니처 기반의 무선 침입 탐지 시스템에 관한 연구)

  • Park, Sang-No;Kim, A-Yong;Jung, Hoe-Kyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.5
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    • pp.1122-1127
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    • 2014
  • WLAN is affordability, flexibility, and ease of installation, use the smart device due to the dissemination and the AP (Access Point) to the simplification of the Office building, store, at school. Wi-Fi radio waves because it uses the medium of air transport to reach areas where security threats are always exposed to illegal AP installation, policy violations AP, packet monitoring, AP illegal access, external and service access, wireless network sharing, MAC address, such as a new security threat to steal. In this paper, signature-based of wireless intrusion detection system for Snort to suggest how to develop. The public can use hacking tools and conduct a mock hacking, Snort detects an attack of hacking tools to verify from experimental verification of the suitability of the thesis throughout.

Adaptive Filtering Processing for Target Signature Enhancement in Monostatic Borehole Radar Data

  • Hyun, Seung-Yeup;Kim, Se-Yun
    • Journal of electromagnetic engineering and science
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    • v.14 no.2
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    • pp.79-81
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    • 2014
  • In B-scan data measured by a pulse-type monostatic borehole radar, target signatures are seriously obscured by two clutters that differ in orientation and intensity. The primary clutter appears as a nearly constant time delay, which is caused by internal ringing between antenna and transceiver in the radar system. The secondary clutter occurs as an oblique time delay due to the guided borehole wave along the logging cable of the radar antenna. This issue led us to perform adaptive filtering processing for orientation-based clutter removal. This letter describes adaptive filtering processing consisting of a combination of edge detection, data rotation, and eigenimage filtering. We show that the hyperbolic signatures of a dormant air-filled tunnel target can be more distinctly enhanced by applying the proposed approach to the B-scan data, which are measured in a well-suited test site for underground tunnel detection.

(Content-Based Video Copy Detection using Motion Directional Histogram) (모션의 방향성 히스토그램을 이용한 내용 기반 비디오 복사 검출)

  • 현기호;이재철
    • Journal of KIISE:Software and Applications
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    • v.30 no.5_6
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    • pp.497-502
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    • 2003
  • Content-based video copy detection is a complementary approach to watermarking. As opposed to watermarking, which relies on inserting a distinct pattern into the video stream, video copy detection techniques match content-based signatures to detect copies of video. Existing typical content-based copy detection schemes have relied on image matching which is based on key frame detection. This paper proposes a motion directional histogram, which is quantized and accumulated the direction of motion, for video copy detection. The video clip is represented by a motion directional histogram as a 1-dimensional graph. This method is suitable for real time indexing and counting the TV CF verification that is high motion video clips.

Implementation of Automatic Worm Signature Generator in DHT Network (DHT 기반 네트워크의 웜 시그니쳐 자동 생성기의 구현)

  • Kim, Ji-Hun;Lee, You-Ri;Park, Dong-Gue;Oh, Jin-Te;Jang, Jong-Soo;Min, Byeong-Jun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.6
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    • pp.1206-1213
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    • 2006
  • Fast detection and automatic generation of worm signatures are essential to contain zero-day worms because the speed of self-propagating worms is too fast for humans to respond. In this paper, we propose an automatic signature generation method against worm's attack, and show the effectiveness of the proposed method by implementing it and appling it to the DHT based network and generating the worm signatures for it.

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Signature-based Mobile Malware Detection Module for Information Security (정보유출 방지를 위한 Signature 기반의 모바일 악성코드 탐지 모듈)

  • Lee, Sang-Ji;Jee, Jung-Eun;Shin, Yong-Tae
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06c
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    • pp.298-300
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    • 2012
  • 세계적으로 스마트폰 이용인구가 증가함에 따라 모바일 악성코드를 통한 정보유출이 빈번히 발생되고 있다. 유출된 정보는 금전적 이득을 얻기 위해 악의적으로 사용되고 있으며, 피해 사례는 지속적으로 증가하고 있다. 제안하는 모바일 악성코드 탐지 모듈은 모바일 사용자의 정보유출을 방지하기 위해 Signature 방법을 사용한다. 또한, 새로운 애플리케이션의 설치 전과 설치 후의 정보를 DB로 저장하여 악성코드 감염 여부를 모니터링한다. 정보유출을 방지하기 위한 모바일 악성코드 탐지 모듈은 사용자의 정보를 안전하게 보호하여 신뢰할 수 있는 스마트폰 사용 환경을 마련해준다.

Quantification of void shape in cemented materials

  • Onal, Okan;Ozden, Gurkan;Felekoglu, Burak
    • Computers and Concrete
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    • v.7 no.6
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    • pp.511-522
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    • 2010
  • A color based segmentation procedure and a modified signature technique have been applied to the detection and analyses of complicated void shapes in cemented materials. The gray-scale segmentation and available signature methods were found to be inefficient especially for the analyses of complicated void shapes. The applicability of the developed methodology has been demonstrated on artificially prepared cemented materials made of self compacted concrete material. In order to characterize the void shapes in the investigated sample images, two new shape parameters called as coefficients of inclusion and exclusion have been proposed. When compared with the traditional use of the signature method, it was found that the methodology followed herein would better characterize complicated void shapes. The methodology followed in this study may be applied to the analysis of complicated void shapes that are often encountered in other cementitious materials such as clays and rocks.

Algorithm for Detecting Malicious Code in Mobile Environment Using Deep Learning (딥러닝을 이용한 모바일 환경에서 변종 악성코드 탐지 알고리즘)

  • Woo, Sung-hee;Cho, Young-bok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.306-308
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    • 2018
  • This paper proposes a variant malicious code detection algorithm in a mobile environment using a deep learning algorithm. In order to solve the problem of malicious code detection method based on Android, we have proved high detection rate through signature based malicious code detection method and realtime malicious file detection algorithm using machine learning method.

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A Development of Malware Detection Tool based on Signature Patterns (시그너처 패턴기반의 악성코드 탐색도구의 개발)

  • Woo Chong-Woo;Ha Kyoung-Hui
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.6 s.38
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    • pp.127-136
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    • 2005
  • Recently, the damages occurring from the malware are increasing rapidly, regardless of continuous development of commercial vaccines . Generally, the vaccine detects well-known malware effectively, but it becomes helpless without any information against the unknown ones. Also, the malware generates its variations fast enough, so that the vaccine always gets behind in its updates. In this paper, we are describing a design and development of malware detection tool, which can detect such malware effectively. We first analyze the general functionality of the malware, and then extracts specific signatures. Such that, we can actively cope with a malware, which may come in previous type, a new type, and any of its mutations also.

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