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스테가노그래피 소프트웨어 분석 연구 - 성능 비교 중심으로

Steganography Software Analysis -Focusing on Performance Comparison

  • Lee, Hyo-joo (Graduate School of Information Security, Sejong Cyber University) ;
  • Park, Yongsuk (Graduate School of Information Security, Sejong Cyber University)
  • 투고 : 2021.08.19
  • 심사 : 2021.08.27
  • 발행 : 2021.10.31

초록

스테가노그래피는 데이터 안에 데이터를 은폐하는 기술로, 전달 매체의 존재가 발각되지 않도록 하는 것이 주요목적이다. 현재 스테가노그래피 관련 연구는 알고리즘을 기반으로 정립된 은닉 기법, 검출 기법들에 관련해서 다양하게 연구되고 있지만, 소프트웨어 성능을 분석하기 위한 실험 중심의 연구는 상대적으로 부족하다. 본 논문은 서로 다른 알고리즘으로 데이터를 은폐하는 다섯 개의 스테가노그래피 소프트웨어의 특징을 파악하고, 평가하는 데 목적을 두었다. 스테가노그래피 소프트웨어의 성능 조사를 위하여 시각 평가 척도로 사용되는 PSNR(Peak Signal to Noise Ratio), SSIM(Structural SIMilarity)을 이용하였다. 스테가노그래피 소프트웨어를 통하여 임베딩한 스테고 이 미지들의 PSNR, SSIM을 도출하여 정량적 성능 비교 분석한다. 평가 척도에 따라 우수한 스테가노그래피 소프트웨어를 소개하여 포렌식에 기여 하고자 한다.

Steganography is a science of embedding secret data into innocent data and its goal is to conceal the existence of a carrier data. Many research on Steganography has been proposed by various hiding and detection techniques that are based on different algorithms. On the other hand, very few studies have been conducted to analyze the performance of each Steganography software. This paper describes five different Steganography software, each having its own algorithms, and analyzes the difference of each inherent feature. Image quality metrics of Peak Signal to Noise Ratio (PSNR) and Structural SIMilarity (SSIM) are used to define its performance of each Steganography software. We extracted PSNR and SSIM results of a quantitative amount of embedded output images for those five Steganography software. The results will show the optimal steganography software based on the evaluation metrics and ultimately contribute to forensics.

키워드

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