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Journals / Natural and Engineering Sciences / 2016 / Cilt: 1 - Sayı: 1

Grayscale Image Authentication using Neural Hashing

Yakup Kutlu
Apdullah Yayık
Pages
23–31
Publication Date
2016-02-03
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

These features are dominant reasons for preferring against traditional ones.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Many different approaches for neural network based hash functions have been proposed.
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Key Findings & Data:Proposed hash function generates hash values using neural network one-way property and non-linear techniques.
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Conclusion & Impact:These features are dominant reasons for preferring against traditional ones.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Image Authentication · Cryptology · Hash Function

Abstract

Many different approaches for neural network based hash functions have been proposed. Statistical analysis must correlate security of them. This paper proposes novel neural hashing approach for gray scale image authentication. The suggested system is rapid, robust, useful and secure. Proposed hash function generates hash values using neural network one-way property and non-linear techniques. As a result security and performance analysis are performed and satisfying results are achieved. These features are dominant reasons for preferring against traditional ones.

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Cite This Article

Kutlu, Y., Yayık, A. (2016). Grayscale Image Authentication using Neural Hashing. Natural and Engineering Sciences, Cilt: 1 - Sayı: 1, 23–31. https://ajindex.com/articles/793298

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