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Attack Detection on Images Based on DCT-Based Features

첫 페이지 보기
  • 발행기관
    한국경영정보학회 바로가기
  • 간행물
    Asia Pacific Journal of Information Systems KCI 등재 SCOPUS 바로가기
  • 통권
    제31권 제3호 (2021.09)바로가기
  • 페이지
    pp.335-357
  • 저자
    Nirin Thanirat, Sudsanguan Ngamsuriyaroj
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A399719

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초록

영어
As reproduction of images can be done with ease, copy detection has increasingly become important. In the duplication process, image modifications are likely to occur and some alterations are deliberate and can be viewed as attacks. A wide range of copy detection techniques has been proposed. In our study, content-based copy detection, which basically applies DCT-based features for images, namely, pixel values, edges, texture information and frequency-domain component distribution, is employed. Experiments are carried out to evaluate robustness and sensitivity of DCT-based features from attacks. As different types of DCT-based features hold different pieces of information, how features and attacks are related can be shown in their robustness and sensitivity. Rather than searching for proper features, use of robustness and sensitivity is proposed here to realize how the attacked features have changed when an image attack occurs. The experiments show that, out of ten attacks, the neural networks are able to detect seven attacks namely, Gaussian noise, S&P noise, Gamma correction (high), blurring, resizing (big), compression and rotation with mostly related to their sensitive features.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Conceptual Background
2.1. Discrete Cosine Transform
2.2. Image Attacks
2.3. DCT-Based Feature Extraction Techniques
2.4. Evaluation Metrics
Ⅲ. Related Work
3.1. DCT-Based Techniques
3.2. Some Other Techniques
3.3. Novelty of the Research
Ⅳ. Proposed Method
4.1. Proposed Method Details
4.2. Method Implementation
Ⅴ. Experimental Results
5.1. Experiment 1: Finding Attack Patterns to Features Relations
5.2. Experiment 2: Attack Detection Using Neural Networks
5.3. Result Comparison: Robustness-Sensitivity and Machine Learning Experiments
Ⅵ. Concluding Remarks
6.1. Contributions of Our Work

저자

  • Nirin Thanirat [ Ph.D. Candidate, Faculty of Information and Communication Technology, Mahidol University, Nakhonpathom, Thailand ] Corresponding author
  • Sudsanguan Ngamsuriyaroj [ Associate Professor, Faculty of Information and Communication Technology, Mahidol University, Nakhonpathom, Thailand ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국경영정보학회 [The Korea Society of Management information Systems]
  • 설립연도
    1989
  • 분야
    사회과학>경영학
  • 소개
    이 학회는 경영정보학의 연구 및 교류를 촉진하고 학문의 발전과 응용에 공헌함을 목적으로 합니다.

간행물

  • 간행물명
    Asia Pacific Journal of Information Systems
  • 간기
    계간
  • pISSN
    2288-5404
  • eISSN
    2288-6818
  • 수록기간
    1990~2026
  • 등재여부
    KCI 등재,SCOPUS
  • 십진분류
    KDC 325 DDC 658

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