Authentication of Quran Verses Sequences Using Deep Learning

Abstract

The emergence of electronic copies of the Holy Quran has allowed an increase in the phenomenon of reading and sharing Arabic verses among internet users. The Quran has been brought together in one book to maintain the order and integrity of its content. Changing the order of verses is considered as a degradation of the Holy Quran, resulting in new surahs in the form of a new composition, contradicting the structure and meaning of what is in the Ottoman Quran. Similar to any verification methodology, this study aims to apply deep learning algorithms to automatically authenticate the integrity of the Quranic content arrangement. The Long Short-Term Memory (LSTM) algorithm was chosen in this work, and the results achieved a test accuracy of 99.98% on the dataset that we created using Tanzil website data.