Volume-10 , Issue-4 , Oct 2022, ISSN 2321-3256 (Electronic Version) Go Back

• Open Access   Article

  A Comparative Study Between RIPEMD160 and SHA256 Hash Functions On Digital Holy Quran Integrity Verification

  N.M. Al-Aidroos, H.S. Baqtian

  Research Paper | Journal (IJSRNSC)

  Vol.10 , Issue.4 , pp.1-7, Oct-2022

  Abstract

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  Abstract
  In Data Security and Cryptography areas, hash functions play a fundamental and important role in the field of Integrity, This paper presents a performance evaluation of two cryptographic hash functions SHA256 and RIPEMD160 which used to verify the integrity of digital holy Quran and determine which one is better. SHA256 and RIPEMD160 hash functions have been selected in this comparison because their characteristics speed and space characteristics, both hash functions have their own advantages and disadvantages what distinguishes them from others, which will be discuss in detail in Background section. This study focuses on security and performance analysis. Security analysis where many experiments be applied to find out the strength and effectiveness of each two hash functions and hash collisions be analysed. The performance analysis will be applied by measuring the speed of the proposed methods in this study. The results show that the RIPEMD160 hash function is faster than SHA256 hash function for the integrity verification on a digital copy of the Holy Quran.

  Key-Words / Index Term
  Integrity, Holy Quran, SHA256, RIPEMD160, Hash Function, Data Security, Verification

  References
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  Citation
  N.M. Al-Aidroos, H.S. Baqtian, "A Comparative Study Between RIPEMD160 and SHA256 Hash Functions On Digital Holy Quran Integrity Verification," International Journal of Scientific Research in Network Security and Communication, Vol.10, Issue.4, pp.1-7, 2022

• Open Access   Article

  Application of Adaptive Neuro-Fuzzy Inference Systems in Mobile’s Spam

  Jyoti Chouhan, Raju Barskar, Uday Chourasia

  Review Paper | Journal (IJSRNSC)

  Vol.10 , Issue.4 , pp.8-11, Oct-2022

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  The function of science is to explain reality logically. With the increased usage of the internet, spamming is the most typical problem that we faced every day. Service of mailing and web applications are much spammed, nowadays this expansion in the number of spam messages has turned into a significant issue. Accessibility of messaging services for a minimal price has come about in the expansion of spam messages. Spam location is attempting a direct result of the necessity for semantic analysis of the compact spam messages, which overall will for the most part have overlapping polarities. In this work, a portable spam order strategy is created in light of an Adaptive Neuro Inference System(ANFIS) containing Gini record fuzzy and Back-Propagation in machine learning. The methodology includes Gini’s index models for information indexes and a back-propagation-based neural network as the AI classifier. This paper presents the assessment of the introduced system based on the error, accuracy of classification, and the number of iterations.

  Key-Words / Index Term
  Mobile Spam Classification, ANFIS, Gini’s Index, Back Propagation, Training Iterations, Classification Accuracy

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  Citation
  Jyoti Chouhan, Raju Barskar, Uday Chourasia, "Application of Adaptive Neuro-Fuzzy Inference Systems in Mobile’s Spam," International Journal of Scientific Research in Network Security and Communication, Vol.10, Issue.4, pp.8-11, 2022