Tamper Detection and Localization for Quranic Text Watermarking Scheme Based on Hybrid Technique

: The text of the Quran is principally dependent on the Arabic language. Therefore, improving the security and reliability of the Quran’s text when it is exchanged via internet networks has become one of the most difficult challenges that researchers face today. Consequently, the diacritical marks in the Holy Quran which represent Arabic vowels ( ) known as the kashida (or “extended letters”) must be protected from changes. The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR), and Normalized Cross-Correlation (NCC); thus, the location for tamper detection accuracy is low. The gap addressed in this paper to improve the security of Arabic text in the Holy Quran by using vowels with kashida. To enhance the watermarking scheme of the text of the Quran based on hybrid techniques (XOR and queuing techniques) of the purposed scheme. The methodology propose scheme consists of four phases: The first phase is pre-processing. This is followed by the second phase where an embedding process takes place to hide the data after the vowel letters wherein if the secret bit is “1”, it inserts the kashida but does not insert the kashida if the bit is “0”. The third phase is an extraction process and the last phase is to evaluate the performance of the proposed scheme by using PSNR (for the imperceptibility), and NCC (for the security of the watermarking). Experiments were performed on three datasets of varying lengths under multiple random locations of insertion, reorder and deletion attacks. The experimental results were revealed the improvement of the NCC by 1.76%, PSNR by 9.6% compared to available current schemes.

In this paper, the author presents a scheme for improving the embedding imperceptibility and security through the use of tamper detection and location authentication of a Quranic text watermarking scheme based on vowels with kashida using the exclusive-or (XOR) and queuing techniques. The proposed scheme utilizes the Queuing technique which was chosen in order to check the embed phase for the tamperage of words forms the text of the Quran's text. As a result, when any of type of attacks such as deletion, insertion, or reordering is detected one can then truly say whether or not the text was, indeed, tampered with, check by extract phase. The main contribution is the development of an improved tamper detection scheme. Thus, this contribution is different from other similar approaches of existing literature due to the addition of the location of authentication in Quranic text watermarking. The proposed scheme was implemented to detect tamperage by a hacker that tried to manipulate the watermarked Quranic text. The use of the hybrid technique refers to using both the XOR and the Queuing techniques which make the proposed scheme more secure in terms of fast and accurate tamper detection. The proposed scheme was able to detect the location of the insertion, deletion and reordering of the tamperage accurately.
This paper contains ve more sections. Section 2 provides related work. Section 3 presents the proposed methods and evaluation. Section 4 discusses the comparison and results, and nally, Section 5 offers the researcher's conclusions.

Related Work
Obtaining the authentication and credibility of users and information through the internet is vital. However, ensuring the Quran's text remains authentic is even more vital. The authenticity and originality of verses in digital media can be challenging to preserve especially as it is prerequisite for accomplishing this feat in a quick manner. The proposed method for implementing a Quranic authentication system is based on information retrieval techniques and hashing algorithms. The evaluation of different characteristics may impact the accuracy of the authentication process. Results showed that hashing veri cation is a good candidate for automatic authentication with high con dence. As a result, rather than focusing on encryption, the primary focus is on authenticating information. However, nding proper Quranic documents online for this research is dif cult; consequently, the relationship between information providers and readers is not typical e-commerce, one-to-one relationship in which typical hash algorithms can be sent to the known receiver. Nevertheless, private keys intended for a receiver will not be applicable in our scenario where the tool is expected to quickly check the Internet for authentic Quranic documents that have not been tampered with [8][9][10].
Tamper detection in plain text papers uses a zero-watermarking algorithm. The algorithm produces a watermark dependent on the quality of the text which can later be obtained using the extraction algorithm to de ne the tampering position in the document. Watermark matching patterns and watermark distortion rates on several text samples of varying duration are used as measurement parameters. Findings show that this algorithm still detects tamperage even when the amount of it is limited. With the limited volume of attack, the presence of a watermark and the reliability of the details are, therefore, dif cult to determine [11].
A zero-watermarking method used for authentication utilizes the characteristics of the Arabic characters without changing the le. The watermark key focuses on the characteristics of the original verses For each verse of the Quran in the initial stage, a key is produced which checks the name and number of the surah along with its ayat or verse numbers. The key is then matched with one that is stored at the certi cation authority. The ndings demonstrate the success of this method in detecting random tampering attacks that include 100% detection of any distortions or modi cations rendered to the Quran's text whether intentionally or unintentionally. Thus, the text should be examined in the event of any discrepancies as shown in Fig. 1 [12].
Some researchers suggest using a tamper locating algorithm for authentication of the content found in .docx documents. The authentication information that is not connected to the text content is stored in the key setting le called document.xml through the segmentation of the display characters. Identifying the quality of the text content can detect whether or not the embedded watermark is similar to the authentication watermark. Tests show that the algorithm is very sensitive to any change and can very well identify the manipulated places [13].
Authentication of image content is primarily used to determine the validity of image content and can easily locate the tampered area in order to determine the motive for actions. Therefore, for content-preserving processes such as noise, compression, and replacement methods, the authentication algorithm must be robust and made vulnerable to malicious attacks. Furthermore, semi-fragile digital watermarking techniques can, to some degree, differentiate between content-preserving activities and malicious tampering attacks [14].
Referring to multiple watermarking systems to secure ownership and tamper detection, this scheme robustly embeds the watermark details used for authenticating copyright by the synonymous replacement process; thus, it uses a double fragile watermark to achieve the detection and position of manipulations. The suggested system has a strong bene t when it comes to its implementation; however, are already some shortcomings such as the watermark's robustness, the precision of nding the tamperage when dealing with a more complicated attack, both of which need further developments [15].

Figure 1:
The authentication system of Quran verses [12] According to the novel CNN-based security-guaranteed image watermarking generation scenario for smart city applications, the content-based watermark synchronization scheme recognizes watermark embedding positions via stable image feature points in the present anti-geometric attack watermarking algorithm, embeds the watermark in a local neighbourhood feature point, and uses the feature points to locate the watermark. These methods demonstrate increased robustness. The gradient path distribution of the neighbouring pixels of a feature point is used to determine the direction information for each feature point. In practice, in a neighbourhood window based on the feature points, samples are generated, and a histogram is used to measure the gradient directions of the adjacent pixels. Thus, with the main direction of the feature point, the peak of the histogram represents the primary direction of the neighbourhood gradient. The model achieves enhanced robustness with the incorporation of CNN [16].
The quaternion Fresnel transform (QFST), computer-generated hologram (CGH) and twodimensional Logistic-adjusted-Sine map (2D-LASM) techniques, a novel four-image encryption scheme is proposed. Four images are in the proposed process, Holistically processed in a vector manner by rst using QFST. Then, using virtual RPM, phase-shifting interferometry (PSI) and Burch's coding process, the encrypted CGH of the input complex amplitude, which is constructed by the components of the QFST-transformed images, is generated [17].
The RPMs are in order to avoid using the entire RPMs as the decryption keys 2D-LASM produced. LASM's initial values are used as decryption keys. CGHs have the advantage of digital fabrication, storage and transmission compared to traditional optical holography. Subsequently, the obtained CGH is permitted based on LASM to improve security. Numerical simulations show the feasibility and performance of the proposed system. The encrypted hologram is scrambled based on 2D-LASM to enhance the security of this paper and weaken the correlation. The validity of the proposed technique of image encryption is demonstrated by experiments [17].
The 2D Fuzzy C-Means (FCM) algorithm has been widely used for segmenting medical images. Throughout the years, various extensions of it were proposed. A modi ed version of FCM was therefore proposed for segmenting 3D medical volumes, which has rarely been implemented for 3D medical image segmentation. We present a parallel implementation using the Graphics Processing Unit of the proposed algorithm (GPU). Researchers state that when working with 3D models, reliability is one of the primary problems when using FCM for medical imaging [18].
A hybrid parallel implementation of FCM is therefore suggested for removing volume objects from medical les. Using actual medical data and virtual phantom data, the proposed algorithm has been validated. The key factors for the device validation were segmentation accuracy of prede ned datasets and actual patient datasets. To demonstrate the ef ciency of each implementation, the processing times of both the sequential and the parallel implementations are calculated. The results obtained conclude that the parallel implementation is 5x faster than the sequential version of the same operation. Concentrate on automatically segmenting oblique slices from 3D volumetric data. To minimise the processing time here as much as possible, an acceleration mechanism using the GPU will be considered [18].
Watermarking systems have been implemented before, but authentication and tamper detection are still a major research issue. A double image-based watermarking scheme was introduced using the Local Binary Pattern (LBP) to protect multimedia documents from unauthorized alteration. The suggested approach involves the following procedure: the host image is partitioned into non-overlapping blocks during watermark encoding. This is followed by the generation of the process vector (S) using LBP and secret watermark bits to execute XOR. A two-bit authentication code is created from the (S) vector and embedded in a dual image based on a shared secret key (ÿ). The ndings are compared to state-of-the-art approaches to show the usefulness of our suggested system. It is noted that the proposed scheme is secure and robust against different standard attacks whereas it can detect the integrity of messages inside the watermarked item [19].
Different scenarios have recently been proposed by the researchers depending on the insertion of variable numbers of kashida per word. Such strategies have produced better results in terms of capacity and security than the previous methods; however, they also reveal a noticeable weakness in the process of retyping [20]. These two forms are designed to provide the working memory for the cover sharing. This can be very useful because the secret posts are created without giving any preference to the user. These two suggested patterns for the secret stocks are hidden within the texts using the Arabic script features to conceal the information based on the extension of the kashida. Moreover, two optimization models are suggested that used the kashida to hide the secret stocks in various scenarios. The enhancement is focused on using the bilocation of the kashida possibilities for the embedding of hidden data within the text. The kashida locations of the rst form are considered to lead to the second form, then to the third one, the fourth one and so on as depicted in Fig. 2.

Figure 2:
The counting-secret sharing process-based rst approach [20] Previous literature shows research has been conducted on text watermarking approaches and methods that were proposed for several purposes of information security. Some research proposes a robust content authentication method for paper text documents, solving the problem of paper document content integrity veri cation, tamper identi cation and tamper position locating. Furthermore, in this method, the watermark information does not depend on the additional carrier, and the text document is embedded with the watermark visible. The watermark is embedded during the process of a printout, which avoids the risk of malicious tampering of the watermark information. As a result, this method is seen to possess high-security performance. The watermarking algorithm is robust against the print-and-scan attack and has a high capacity with low accuracy. In addition, the minimum string edit distance algorithm is used to compare the difference between the authentication watermark signal sequence extracted from the scanned image and the one calculated in real-time, through which it determines whether or not the paper document's text content has been changed, and if so, it accurately locates the place where it was tampered with [21].
The Intrusion Detection System (IDS) is an application that detects malicious attacks or data breaches within a network. As a vital network security element, IDS has been frequently used in recent years. This analysis aims to de ne the best-t solution, that would reduce the number of features substantially. Furthermore, with less processing time, the method would lead to high classi cation accuracy. We propose a hybrid feature selection model that combines the strengths of the legacy ltered and wrapper selection mechanism to reach this aim. This proposed amalgam of approaches is supposed to ef ciently pick the optimal set of intrusion detection features. Using correlation feature selection (CFS) along with three different search techniques known as best-rst, greedy stepwise and genetic algorithm, the suggested hybrid model was carried out [22].
In order to evaluate each of the features that were rst selected by the philtre process, the wrapper-based subset evaluation uses a random forest (RF) classi er. On both the KDD99 and DARPA 1999 datasets, the reduced feature range was checked in a supervised setting using an RF algorithm with ten-fold cross-validation. The outcome shows that, in terms of detection time, accuracy, and detection rate, choices made by the hybrid feature had better performance improvements. A low false alarm rate was reported, as well [22].
The suggested zero watermarking utilized the material features of the text to create a watermark instead of embedding the watermark in the text using the structural variable and word length, that is common to all kinds of texts. It consisted of two stages: text embedding and extracting. The watermark was generated with the data holders, and the extraction was done with the certifying authority (CA) [23]. The architecture of the proposed tampering detection scheme is shown in Fig. 3.  A technique was developed that used a text document as an input for manipulation detection, and the watermark was created based on the HSW (hybrid structural component and word length) approach. A watermark extracted pattern was registered with the (CA) where the attacker could change the document's contents. During the tampering identi cation, the extraction method was used to retrieve the watermark and the template tted the recorded (CA) model. A decision on the interference was made that depended on the degree of pattern matching with MD5 compression. The evaluated attacks including the deletion, insertion, and reordering using this method achieved high accuracy than other works and. However, this approach could not update the detailed ownership of the source in the generated watermark information [24].
The proposed zero-watermarking technique known as watermark arrangement is based on the Markov Model Level 4 Word Mechanism (ZWAFWMMM) and is used for authenticating information and detecting tamperage within the Arabic text. It is an effective model as ZWAFWMMM adopts a hybrid system. Nevertheless, due to the complicated nature and structure of the Arabic language, the basic curriculum uses conventional techniques which lack the capacity to provide effective solutions to the Arabic text. The ndings of the experiment reveal that ZWAFWMMM is more sensitive to all forms of tampering and highly accurate when it comes to the low capacity of tamper detection [25].
As mentioned before, the Holy Quran is a religious book that plays an extremely vital role in the life of Muslims as the main decisions of Islamic jurisprudence and, indeed, the everyday life of Muslims are based on the instructions written in the verses of the Holy Quran. Ordinary Muslims cannot judge the authentication of the verses of the Holy Quran if the verses have been tampered with. In fact, it requires intense attention, extensive knowledge, and dedicated efforts to be able to tell the difference between true Quranic verses and ones that have been tampered with, especially when one or more words are missing from the recitations. Typically, the authenticity of an online quote attributed to the Quran can be con rmed by making a comparison between the online quotations and the original text of the Quran [26]. Furthermore, the Holy Quran is written in Arabic language and with various styles, such as plain text, Uthmanic, Kou , Kaloon, and other such styles [26]. These styles are also used in the Middle East and all Muslim countries. However, Tab. 1 mentions the current comparison studies with other baseline approaches.

Proposed Watermarking Method
The methodology used in this research is divided into four phases: The rst phase is the pre-processing phase which, as its name suggests, is responsible for the preparation of the hosting media such as the Quranic text in this case, and a secret bit (data that was hidden in the text). The second phase includes the embedding of the secret bit within the Quranic text. The third stage involves the extraction of the data including the attack process and the nal phase is the performance evaluation of the scheme through the use of various measures. The details of each phase are discussed below.

Pre-Processing Phase
In this phase, the watermark is converted from the binary image into the sequence of bits by decoding it with certain conditions (e.g., inserting a kashida in the next letter after the vowel).
Next, the binary image is scanned to sequentially nd the byte. If the byte value is 255, then the secret bit is 0. After nishing the binary image scan and byte assignment, vector 1 and 0 are produced. During this phase, the original Quranic text is called the cover text. This text consists of various characters that are given a unique ASCII code with a decimal value. This decimal's value is useful for determining the condition of embedding which is known in advance. Each location is stored in the vector-based condition accordingly and produces the vector for the position as shown in Fig. 4. After this process, the pre-processing phase was completed that covered the Quranic text with a secret bit ready for the embedding in the next phase.

Embedding Phase
The proposed scheme is based on the vowels to be embedded in the Arabic text where the three vowels are used. These letters are selected because they are the most redundant characters in the whole text of the Quran. The embedding process is comprised of the preparation phase for both watermark and covers of the Quranic text. For watermarked text, all the bytes are converted into bits and then stored in the vector. The cover of the Quranic text should scan rst for counting several vowels and check the condition (inserting a kashida in the next letter after the vowel) that is appropriate with the embedding protocol.
The embedding strategy is accomplished in the following six steps: • Prepare both watermark and cover Quranic text. The preparation step is necessary for any watermarking scheme which is comprised of two elements.
• Prepare the watermark for conversion into binary decomposition in the form of 1 and 0 that results in secret input of the system as a serial of bits.
• Prepare the Quranic text including manipulating the text as the UTF le format before embedding to make it compatible with the ASCII code and further control.
• Open text le to check if there are vowel letters and then save them in vector.
• Match secret bits with the condition (inserting a kashida in the next letter after the vowel). If matching greater than secret bits then invert the secret bits that are obtained from the watermark (0 → 1 & 1 → 0).
• Apply the embedding process by adding the kashida character when the secret bit is 1 otherwise do not add it.
• Embed to satisfy the condition of the rst vowel letter to hold the secret bit (as kashida).
• After nishing the cover text, prepare the watermark text to send the receiver. Embedment in the proposed scheme with the condition is necessary to ful l the agreement between the sender and receiver as shown in Fig. 5. There are two cases when inserting the bits from the watermark into cover Quranic text which is 1 and 0 depending on the presence or absence of kashida. These four cases control the most embedding issue as summarized in Tab. 2. Results can be interpreted as 1 if the kashida is present in the watermarked text; otherwise, if it is absent, it is represented as 0. The kashida in the original text (cover text) may or may not appear inside. Each byte in the binary image is represented by bit 1 (white) and 0 (black) and these bits are stored in vector to embed it sequentially into the cover text. After locating the vowel letters and insertion into the cover text, the technique checks the condition of the embedding of the letter in the next vowel letter.

Extracting Phase
Although the extraction process includes many special cases, it is the reverse process of the embedding technique. The enclosed complex data inside the watermarked text needs to be arranged according to the embedding and extracting techniques which may be changed by the external effects. The extracting technique is responsible for the action of all these details. The main contribution of the proposed embedding or concealing technique of the secret bits is the insertion of the kashida at the next letter after a vowel. For extracting the hidden information, one needs to nd the vowel letter to locate the next letter. To nd the appropriate kashida position for extracting, the condition for the embedding needs to be checked where the presence or absence of the word's kashida is represented by the secret bit 1 or 0 as shown in Fig. 6. After this phase, a certain letter is converted from the ASCII into the binary bit. These bits are stored in a vector for the next process tamper detection attack as explained below.

Tamper Detection Attack
During the transmission, the watermarked Quranic text suffers from many kinds of attacks and tamper detection is one of them. Tamper detection in the proposed scheme aims to nd any external manipulation that is unauthorized. The recipient does not know whether the watermarked text was tampered with or not. Thus, the proposed scheme detects whether or not the watermarked Quranic text has been tampered with by reading each letter or word throughout the document. Therefore, that which the watermarked text is converted into consists of the decimal value and vector of the decimal value and is examined by taking the highest value found in the text. Next, by examining and analyzing it with the remaining text characters, one of its values is obtained. A le must be opened to store these values where, afterwards, they are read and combined with different techniques to both stores in a vector and also determine their location as well.
Furthermore, the detection of a tampered-with watermarked Quranic text usually shows that the text has been manipulated by the intruder in one or all of three ways. First, the intruder adds either a single letter to the word or adds a single word to the statement to confuse the recipient of the watermarked Quranic text. Second, the intruder deletes one letter in the word or one word in the sentence, which affects the meaning of the sentence. However, quite often, it is an unimportant letter in the text that the intruder seeks to modify. Moreover, the deletion or shifting of such a letter does not change the whole meaning of the word or statement. Depending on the nature of the language, it is important to work with some letters that have no meaning or are often aesthetically located within the text. Third, the intruder often manipulates the letters in the word or sentence to trick the receiver and becomes successful due to the similar-looking shape and size of the original text in the watermarked Quran. If detected the le must be read again, otherwise, the scheme is claimed to be successful.
In the present study, the proposed scheme nds there are three types of tampering and resolves the drawback of the existing methods for tamper detection inside the program as mentioned above. Thus, two techniques are included in the proposed scheme for controlling tamper detection. These include the queuing technique with the FIFO process and the XOR operation to check changes in the watermarked Quranic text as discussed below.
Queuing Technique The main aims of watermarking schemes are to conceal the secret bit in the cover Quranic text. This is rst done on the sender's end to produce the watermarking of the text. It is then sent through the trusted channels to the receiver for extracting the original secret text. The receiver's side is responsible for receiving the data and is not aware of the missing part in the received data. For this reason, some missing information may contain a secret bit; therefore, it is important to keep an eye out for any information which might be lost during this time. Sensitive data should be integrated and there is no way to proceed without every bit of information in its wholeness. Thus, the queuing technique is proposed to track each letter and word between the sender and receiver. The main issue here is to detect the presence of any tamperage in the text of the Quran wherein any text represented in the digital world as the ASCII code (hexadecimal) must be converted into a binary representation (a serial of bits). These bits involve the words and statement (whole text). Logically one can depict this compensation as a queue Fig. 7.
The queue looks like a 2D array where the rows represent a place of words with each cell consisting of a letter. Every word located in a single row, along with the number of rows in this array, considers the whole text. The last bit in the row speci es the results of the XOR operation, where the last bit in the vector that denotes the XOR of all the bits in the end or rows mentioned before. On the receiver side, the whole text is received as one package and the receiver reads it word for word or even letter for letter. Consequently, the architecture of the text of the Quran looks like queue letter by letter representing the word (raw of the queue) and word by word to represent the statement (verses) or the whole text (column of the queue). The receiver manipulates the text of the Quran as a serial of bits. Therefore, the absence of one letter or word immediately gets discovered due to the change in the sequence of the queue. The receiver side can catch the original text queue by comparing with the key that contains an index for this queue. However, the tampering or changing of the text of the Quran is easy to discover with its secret information.
The secret key that sends to the receiver should contain the indexing of the queue, wherein the indexing queue consists of the manipulated bits generated from many processes based on the XOR operation. Generally, half of the words (50%) are taken from each row and the XOR with another half of the same word is performed to produce the bits considered as the indexing bits. The same procedure is followed for the rest of the queue and applies to all of the text of the Quran as illustrated in Fig. 8. In the queue, the bits of the word XOR results in the bit store at the end of the row which is checked later by the receiver. Changing or modifying any letter of the word leads to an error in this bit. The same XOR operation is applied to all these bits for all the text (queue) and the results are stored in the secret key.
XOR Operation After embedding, the watermarked Quranic text is sent to the receiver wherein all the embedded secret information is extracted from the watermarked text that is stored in the watermarked key. The watermarked key can carry very little information in this case, and as such, there must be some technique to retrieve as much information as possible. It is known that a proposed scheme that produces one decimal value can be used by another partner to nd the real or original le. This value is considered as the maximum value in the text le extracted from the vector of the queuing technique. After producing this value, the receiver performs the XOR of all the values in the queue with this number inside the key to nd the original text.

Tamper Detection Process
The proposed scheme detects the tampering in the watermarked le by reading each letter or word throughout the document. First, the watermarked text is converted into ASCII and the Figure 8: Process of the queue for the tampering examined by taking the highest value found in the text. Next, by examining and analyzing it with the remaining text characters one of its values is obtained. A le must be opened to store these values and then they are read as well as combined with the XOR to store in a vector. In this event if the tampered text is detected then the le must be read again; otherwise, the scheme is claimed to be successful. Thus, Fig. 9 shows the basic architecture of the proposed tamper detection scheme.
Any text le consists of a group of letters and even space is considered a letter under a certain value. Thus, each text le considers a series of letters that can be viewed as a long vector. The letter or character is coded in the computer in a unique ASCII code which is shown as the decimal value. In fact, a text le is a group of decimal value and each value matches one character in the text le. Consequently, for decoding the letters within text le the decimal value le is created similar to the 2D array or matrix with rows and columns as depicted in Fig. 10 The conversion of the watermarked Quranic text le into the corresponding decimal value is necessary. The decimal values are easy to generate using logical operations such as the XOR, OR, AND, and so on. The basic insight can be obtained from the decimal le which is necessary to secure the process and information itself. If conditions are favourable, the logical process is started. In the proposed scheme, this term refers to the selection of the maximum number or value from the decimal le. This maximum number that is used for the important logical operation is called the Exclusive OR process (⊕).
Moreover, it is worth explaining the details of the XOR operation here. This operation is considered to be the logical operation that accepts two arguments including the digital input and produces one argument result. For more than two arguments one must combine many operations. The XOR operation is mainly applied due to its ease of use, understanding, and ability to acquire input as a result in the second iteration. It implies that if the output result is XOR-ed again with one input argument then one can get the second input argument. On other hand, if only one of p or q is T/1, then the result will be T/1. Otherwise when both p ⊕ q is (F/0) or (T/1) then the result will be F/0. Thus, considered to symbol F = false, and T = true as shown in Fig. 11.

Figure 9: Tamper detection process
After the embedding phase, the authentication process starts with the decimal le and the maximum number of some procedure via the XOR operation. Every number in the decimal le is XOR-ed with the maximum number that is derived from the decimal le for tracking. Consequently, the Queue vector is designed to store the results (decimal le ⊕ MAX value) using the queuing technique. The rst decimal value obtained from the decimal le is XOR-ed with the max value and the results stored in the rst position of the queue vector. The same procedure is used for the next second decimal value and its result is store in the second position of the queue vector. The queue vector generation strategy followed the First In First Out (FIFO) or on a rst-come, rst-served basis. On the sender's side, a vector is produced after embedding which is further used by the receiver to verify the presence or absence of tamperage in the watermarked le before extracting to. After the embedding process, to keep track of the queue vector the reverse procedure is followed in the sender side as displayed in Fig. 12.   After the receiver obtains the necessary information from the watermarked key, the XOR operation is performed to logically generate the queue vector and max value number. This operation results in a decimal le identical to the one derived from the watermarked le. Thus, the procedure of authentication in the system operates like A⊕B = C at the sender side and B⊕C = A at the receiver side (or vice versa).
After nishing the XOR process, the resultant le is compared with the decimal le derived from the watermarked text to identify the presence (or absence) of any differences, indicating the presence (absence) of tampering. This method is very secured, less time consuming and makes it more dif cult for the hackers or intruders to guess the secret key. Using this technique, three main threats can effectively be detected such as the insertion of the outlandish character or deletion of one of the speci c existing characters, or the modi cation or reordering of characters in the text le as explained underneath. Fig. 13 shows the basic design of the proposed tamper detection scheme that reads the secret key and watermarked le on the receiver website. Next, the method examines the vector le from the key in the text. Consequently, it reads both vector and watermarked characters until the entire le is processed. The examination and analyses for the remaining text characters are obtained until the end of the le is processed. Then, it reads again to rectify the presence of any issue related to the processing. In addition, it normalizes the length of les by reading both vector and watermarked characters. When the vector and watermarked characters are combined with the XOR of different values, it implies the successful detection of the tampered text. Thus, the le must be read again. Finally, the scheme writes the le with the position of a mark to detect the location.
In addition, Fig. 14 shows the whole identi cation tamper pseudocode scheme used in the proposed technique.

Evaluation Phase
Every watermarking system aims to evaluate the performance of the resultant watermark media on the sender's side before sending it to the receiver, thereby ensuring the robustness of the proposed scheme against attacks. In this paper, two types of assessment evaluation are used to check the performance of the proposed scheme: First, the Peak Signal-to-Noise Ratio (PSNR) is evaluated to determine the imperceptibility of the watermarked version. The PSNR value re ects the similarities between the watermarked Quranic text with the original. If the PSNR is high then it is easy to deceive the intruder or attacker, implying the absence of secret bit involvement in this media.
The distribution of the secret bit embedded to cover the Quranic text re ects the PSNR value, while the PSNR detect the frequency of the bits within the cover Quranic text. When the bits become heterogeneous or more chaotic, then the PSNR will get high value. Thus, for embedding is introduced. The high PSNR value indicates good quality of the Quranic text, thereby all the previous methods tried to enhance the PSNR [26]. Subjective methods depend on the human eye and assessment without using any reference evaluation. The PSNR value that is used to measure the quality of the text of the Quran after embedding can be de ned as Eqs. (1) and (2): With, where the variable integer MAX is the maximum number of possible letters value of the input text, then MAX is considered one or 255 bytes which means adding the kashida into embedding process when it contains an unsigned 8-bit integer data type. While MAX considers 0 when it does not have any kashida, m: integer value is the range of the whole text, and n: integer variable considers the number of verses; in the other part of the Eq. (1): character variable refers to the original text and K: character variable is the noisy text (watermarked text).

Figure 13: Identi cation tamper process
Since the MSE double variable adversely affects the double variable PSNR, then there will surely be some inevitable harmful effects. The PSNR parameter allows for the normalizing of the equation for all methods and text types. However, measured either as a ratio or as a(log 10) base−10 (decibel) or base−2 (doublings orbits), the logarithmic value of the difference lies between the smallest and largest signal values. For example, the decibel (dB) is a unit used to express the ratio as logarithms, mostly for signal power and amplitude [27].
The second evaluation of the effective performance evaluation of system security for the Quranic text watermarking is the calculation of Normalized Cross-Correlation (NCC) measure. The double variable NCC value re ects the ability of the watermark to withstand against any Figure 14: The whole identi cation tamper pseudocode proposed scheme attack that happened to the watermarked text [28]. The NCC can calculate the similarity between the original watermark W (i, j) and the extracted watermark W (i, j) when using Eq. (2): where n and m are the integer variables represents the range of the text (verses or whole text), i and j are the integer variables refer to the location of the text and letter in such word.
The range of the NCC value is in between 0 and 1 and the watermark is said to be the best when it is very close to 1, indicating the closeness of the extracted watermark character variable (W ) to the original one (W ). The NCC value obtained from the DCT or frequency domain is often lower than the spatial domain because the coef cients in the frequency domain always affect the extracted watermark (W ), thus making it lesser [29]. In image watermarking, the NCC very clear but in the proposed text watermarking scheme a substantial difference from the existing scheme must be achieved. The extracted text of the Quran is rst separated into verses and then the words take characters. By comparing it with the original text of the Quran (W ), if the watermarked text shows a slight difference then it is considered as an abutter method than other approaches; else, the embedding process must be repeated.
However, the material of data used in the Quranic text dataset was acquired from the public domain via the Internet. The Arabic text was obtained from different reported art-of-the-studies for benchmarking. This dataset was selected due to the enclosure of the sensitive data related to Islam. In addition, surahs of different sizes were chosen for the compression of the host text, benchmarking, and evaluation as explained below.

Results and Discussion
The implementation of the proposed scheme has been achieved via the use of MATLAB software. In order to evaluate the performance of the proposed approach, it has been considered the standard and authentic version of Quran datasets from tanzil.net [30]. Likewise, these standards have been used in previous research. This dataset was further veri ed by experts. Moreover, the standard Quran datasets which have been utilized in this work are selected based on the payload capacity and watermark (Logo). The performance evaluation of this work is performed through using four different payload capacity (Al-Kursi verse 4 Kelo bytes (Kb), Surah Al-A'raf 32 Kb, Surah Al-A'raf and Al-Anbiy 43 Kb, Surah Al-Baqara 58 Kb). Consequently, Watermarking of the Four logos in the binary images of such as the H, UTM, Nike, and ( ) . Are chooses randomly dependent on the sizes. Fig. 15 shows the system interface of the proposed scheme based on tamper detection with the location: The system is tested by modifying the output le of the watermarked Quranic text to see if the system can detect this case as illustrated in Fig. 16. This includes the modi cation of the Text of the Quranic text without any sense wherein the text can easily be altered by editing it using any software application.
In Tab. 3, we compare the performance of the proposed scheme in terms of PSNR and NCC values with the existing state-of-the-art methods in the literature. The results revealed that the proposed method outperformed the existing ones in terms of quality and robustness. For a fair comparison, the watermark was used for the testing. The PSNR value for watermark host text was 68.20 dB, displaying about 16 dB quality enhancement compared to the highest reported PSNR value (52.05 dB). In addition, the PSNR value for watermark chess host text was 67.43 dB, indicating a quality increase of 14.5 dB compared to the existing reports (62.94 dB). In short, the improvement was acceptable due to the enhancement of the PSNR by 16 dB over other literature reports.
The NCC value of the proposed method for the watermark host text was 0.9976%, showing the security enhancement of 1.76% compared to the latest related work 0.98%. In (H) host text, the NCC value for the proposed method was higher than the reported nding which is 0.9976%, for the still (H) host text. Thus, the proposed scheme achieved about 1.76% security and accuracy enhancement for the NCC value compared to that reported in the literature.
The results of the measurement performance using PSNR and NCC in this study to improve the accuracy and security are shown in Figs. 16 and 17. Fig. 16 shows the illustrated results of different payload capacity with a xed secret watermark of 25 bytes. The difference (83.06 to 86.12) of about 3 dB in the PSNR at the beginning is due to the small text le size where the reversing mechanism played a remarkable role. However, larger text le sizes (which made up the rest of the cases) allowed for the use of the random   Figure 16: Imperceptibility evaluation using function among the satisfying conditions; thus, the reversing mechanism played an insigni cant role. For large text les as hosting media, more vowels are available to host a secret bit and thus randomly chosen from these letters. The PSNR value is increased with the increase in the le size. The observed sudden increase from one limit capacity to another is because of the excess available space for hosting the secret bits, indicating the embedment of many secret bits and thus making the free space untapped. Fig. 17 shows the varying payload dependent NCC values. Overall, 1344 bytes has the highest NCC value compared to (25,672, and 841) watermarks. This gure also shows that, although there are three different host text le sizes (32000, 43000, and 58000 bytes) used to embed the host text le and test the security of the proposed scheme, 58000 bytes (grey color) has a better result in all host text le size.
The results of NCC as shown in Fig. 18, posit that the Quranic text processing tools have been distributed over the Internet. Because of this easy and free handling, a sensitive document found on the internet such as the Holy Quran is always under the threat of being tampered with  Figure 17: The values of NCC as a function of the different logos with payloads capacity payload capacity obtained using the proposed scheme by intruders or malicious users, causing it, thereby, to lose its authenticity and originality. For many applications, the veri cation of the integrity of such data is important. Therefore, many methods have been proposed over the years to verify the authenticity and integrity of the text of the Quran's content. In this spirit, to keep the text of the Quran far from distortion or tampering a robust watermarking scheme has been proposed to detect all kinds of tampering in advance before proceeding to extract the information.
The benchmark of tamper detection of the proposed scheme compared to other researchers work in the tamper detection attack of the Quranic text-domain is shown in Tab. 4.
Tab. 4 shows the benchmark work with existing researchers' work that mentioned there is tamperage or not. All the host apply by all researchers are from Arabic text. The previse work as shown in Tab. 4. Only detect the status of tamper. However, our proposed scheme improved the ability to show the location tampered as shown here in Fig. 18: Tamper detection is a different procedure from other evaluation criteria in terms of the measures where detection gives the condition of true or false. In the simulation program, the noti cation is received to ascertain the presence or absence of the tamperage. In addition, can   [35] Arabic NA [36] Quran NA Proposed scheme Quran be determined the location of the tamper detection inside the word or statement called tamper identi cation so this process is working when the text has been tampered with.
Indeed, the ef ciency of this scheme that we are focusing on the authentication of the tamper detection and location inside the text watermark than existing works. Therefore, we used 3 datasets to get the best experimental analysis results compared with the benchmark of the currently existing work.

Conclusion
The purpose of this paper is to enhance the watermarking scheme of the text of the Quran based on a hybrid technique (XOR and queuing techniques). The methodology consisted of four phases: The rst phase was the pre-processing phase followed by the embedding process phase which is performed in order to hide the data after the vowel letters where if the secret bit is "1", it inserts the kashida but does not insert the kashida if the bit is "0". The third phase is an extraction process and the last phase is an evaluation of the performance of the proposed scheme by using PSNR for the imperceptibility and NCC for the security of the watermarking. However, in terms of tampering detection, accuracy falls below deletion, insertion, and reordering attacks. The experimental results revealed the improvement of the NCC by 1.76%, PSNR by 9.6% compared to available current schemes. For the future work, researchers should consider the watermarking of the Quranic text when manipulating the text in different formats (.docx, .rtf, and so on) which was out of the scope of this research. Again, some measures that are not mentioned in evaluating the present scheme might also be considered. Many attacks which are not considered in the proposed scheme must be also be looked into. In sum, it is worthwhile to enhance the security and capacity of the scheme for its further betterment.