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Steganography is the art of covered or hidden writing. It is used for criminal activities applications environment. In this paper we focus on implementation of effective detection technique is an essential task in digital images. Previously many number of detection techniques are available for steganography images. After implementation of all approaches also again some challenges are available. This paper presents comparative study in between different steganalysis techniques. Different techniques are providing different results. Analyze of all techniques detection and embedding performance results. Finally we can decide one best steganalysis technique. It saves time and increases accuracy compare to all previous methods.
Rajendraprasad K. 2016. \u201cSteganography Images Detection using Different Steganalysis Techniques with Markov Chain Features\u201d. Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 15 (GJCST Volume 15 Issue G3): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 107
Country: India
Subject: Global Journal of Computer Science and Technology - G: Interdisciplinary
Authors: Rajendraprasad K, Dr. V. B. Narasimha (PhD/Dr. count: 1)
View Count (all-time): 305
Total Views (Real + Logic): 7840
Total Downloads (simulated): 2071
Publish Date: 2016 01, Sun
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Steganography is the art of covered or hidden writing. It is used for criminal activities applications environment. In this paper we focus on implementation of effective detection technique is an essential task in digital images. Previously many number of detection techniques are available for steganography images. After implementation of all approaches also again some challenges are available. This paper presents comparative study in between different steganalysis techniques. Different techniques are providing different results. Analyze of all techniques detection and embedding performance results. Finally we can decide one best steganalysis technique. It saves time and increases accuracy compare to all previous methods.
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