A Dynamic Multi-Layer Steganography Approach Based on Arabic Letters’ Diacritics and Image Layers
Abstract
:1. Introduction
- The dynamic multi-layered concept: Previous research studies primarily focused on specific techniques or a combination of techniques to conceal information, such as using Arabic movements or kashida within texts. However, our work introduces a dynamic multi-layered concept that enables the concealment of secrets of various sizes. This approach provides flexibility and adaptability in hiding information within texts.
- A novel steganography algorithm: We propose a novel steganography algorithm that specifically addresses the method of hiding text with a text cover in different ways and scenarios and then embeds it in a cover image as another layer. By incorporating Arabic diacritics and Hamzas, our algorithm enhances the concealment process and makes it highly challenging for potential attackers to detect hidden information. This algorithm offers improved security and resilience against detection.
2. Related Work
2.1. Image Steganography Methods
2.2. Arabic Text Steganography Methods
- The process of extracting the text requires an optical character recognition (OCR) process to extract it to establish the locations of the variable points in their places, in addition to the fact that a change in font type would lead to complete loss of the embedded data;
- The position of the hidden bits is not random; thus, the predictability can be exploited;
- Low sustainability.
3. The Proposed Approach
Algorithm 1 First Scenario Algorithm |
String Encrypt_First_Scenario(string message, int [] Positions, String Key, String CoverText) |
Start Map [] = Positions []; String Sec_msg = AES.Encrypt(message, Key); Binary [] msg = Convert_To_Binary(Sec_Msg); Int L1 = Length (msg); Int L2 = Count (Map); Int L3 = Find_Count (“ Int Index = 0; If (Map[End] <= L3) If (L1 == L2) While (Index < L1) Bit b = msg[Index]; If (b) CoverText [ Map[Index] ] = “ Else CoverText [ Map[Index] ] = “ End Index ++; End While Else return “Error Mapping”; End IF Else Return “Error Capacity“; End IF Return CoverText; |
End Function |
Algorithm 2 Second Scenario Algorithm |
String Encrypt_Second_Scenario(String message, String Key, String CoverText) |
Start String Sec_msg = AES.Encrypt(message, Key); Binary [] msg = Convert_To_Binary(Sec_Msg); Int L1 = Length (msg); Int L2 = Find_Count (“ أ إ”, CoverText); // Number of all HAMAZAT Int Index = 0; If ( L1 < L2) While (Index < L1) Bit b = msg[Index]; If (b) CoverText [Index] = “ اَ ”; Else CoverText [Index] = “ اِ ”; End Index ++; End While Else return “Error Mapping”; End IF Return CoverText; End Function |
4. Result and Discussion
4.1. Implementation
4.2. The Metrics of Evaluating Steganography
4.2.1. Imperceptibility
4.2.2. Capacity
4.2.3. Robustness
4.2.4. Security
4.3. Experimental and Investigations on the Proposed Method Based on the Steganography Metrics
4.3.1. Hypotheses
- First, Table 6 displays the details of the transcripts utilized in our experiments. Four different texts of lengths and properties were employed.
- Secondly, the secrets were randomly selected and comprise a combination of binary digits (zeros and ones).
- Thirdly, the proposed approach was evaluated by a team of five experts using the five-point Delphi method, where decisions were made based on the majority agreement among the team.
4.3.2. Capacity Feature
4.3.3. Security and Imperceptibility Features
Algorithm 3 for Steganography layers selection. |
Input (cover + secret) Output (hidden secret) Step1: Determine the scenario of choice for hiding secret messages: Diacritics or Hamzas Step2: Calculate the Capacity to determine which scenario has the highest capacity. Step3: Apply Testing for Crypto Analysis and Imperceptibility Criterion to evaluate the effectiveness of the chosen scenario.
Conceal the secret message within the chosen scenario by modifying the necessary characters according to the predefined MAP.
|
4.4. Comparison between the Proposed Method and the Other Methods Based on the Steganography Metrics
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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النطق Pronunciation | الرمز Symbol | الحركة Diacritics | الحرف Letter |
---|---|---|---|
با | فتحة | الباء | |
بو | ضمة | ||
بي | كسرة | ||
ب | سكون | ||
بن | تنوين الفتح | ||
بون | تنوين الضم | ||
بين | تنوين الكسر | ||
ابب | الشدة |
معزولاً Isolated | في أخرها At its End | في أوسطها In its Middle | في أول الكلمة At the Beginning of the word |
---|---|---|---|
ي | ــــي | ـــــيــــــ | يــ |
ك | ــــك | ــــكـــــ | كـــ |
The bit number of the secret message to be hidden | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | … |
The number of the diacritic used in concealment | 1 | 5 | 50 | 70 | 71 | 72 | 80 | 100 | 102 | 104 | 105 | 106 | … |
Password | Key | We Padded the “Key” to 16 Characters by Zeros, or MD5 Can Be Used | |
---|---|---|---|
Secret Message | “Message” | ||
Encrypted Message | U3YeVbnZ6vDUksOOZSoWng== | Note: Many algorithms can be used here RSA, AES, DES, etc. | |
Binary Message | 00011000 01010101 00110011 01011001 01100101 01010110 01100010 01101110 01011010 00110110 01110110 01000100 01010101 01101011 01110011 01001111 01001111 01011010 01010011 01101111 01010111 01101110 01100111 00111101 00111101 | Note: The first 8 bits represent the length of the message, which is 24 = 00011000 The next 8 bits represent the “U” character | |
Cover Text Second Scenario we rely on the Hamza | :تتميّز اللّغة العربيّة عن كافّة اللّغات العالميّة الأُخرى بمجموعةٍ من الخصائص وهي: الأصوات: من المُميّزات الأساسيّة للّغة العربيّة؛ إذ يُعتَبر نظام النّطق فيها من أهمّ أنظمة الكلام اللغويّ، فيُستخدَم اللّسان، والحلق، والحنجرة من أجل نطق الحروف والكلمات بناءً على أصواتها، وتُقسَم الأصوات في اللّغة العربيّة إلى مجموعة من الأقسام، مثل أصوات الإطباق، وأصوات الحنجرة، وغيرها. المُفردات: هي الكلمات التي تتكوّن منها اللّغة العربيّة، ويُصنَّف المعجم اللغويّ الخاص فيها بأنّه من أكثر المعاجم اللغويّة الغنيّة بالمفردات والتّراكيب؛ فيحتوي على أكثر من مليون كلمة. وتُعتبر المفردات الأصليّة في اللّغة العربيّة عبارةً عن جذور ثلاثيّة للكلمات الأُخرى، فينتج الجذر اللغويّ الواحد العديد من الكلمات والمُفردات. كما أن اللفظ بالإعتماد على الحركات والصرف المرتبط بالمفردات وجزورها والنحو الذي يمثل أساس الجملة فيها … كل ذلك مما يمزها عن باقي اللغات. لذلك تُصنّف اللّغة العربيّة كواحدةٍ من اللّغات التي تَحتفظ بنظامٍ نحويٍّ خاصّ بها، ويُساعد في إعراب جُملها وبيان طُرق كتابتها.. | ||
Text after Hiding first 16 bits. We changed 6 characters. (Green) | :تتميّز اللّغة العربيّة عن كافّة اللّغات العالميّة الأُخرى بمجموعةٍ من الخصائص وهي الأصوات: من المُميّزات الأساسيّة للّغة العربيّة؛ إذ يُعتَبر نظام النّطق فيها من اَهمّ اَنظمة الكلام اللغويّ، فيُستخدَم اللّسان، والحلق، والحنجرة من أجل نطق الحروف والكلمات بناءً على أصواتها، وتُقسَم الأصوات في اللّغة العربيّة اِلى مجموعة من الأقسام، مثل أصوات الاِطباق، واَصوات الحنجرة، وغيرها. المُفردات: هي الكلمات التي تتكوّن منها اللّغة العربيّة، ويُصنَّف المعجم اللغويّ الخاص فيها باَنّه من اَكثر المعاجم اللغويّة الغنيّة بالمفردات والتّراكيب؛ فيحتوي على أكثر من مليون كلمة. وتُعتبر المفردات الأصليّة في اللّغة العربيّة عبارةً عن جذور ثلاثيّة للكلمات الأُخرى، فينتج الجذر اللغويّ الواحد العديد من الكلمات والمُفردات. كما أن اللفظ بالإعتماد على الحركات والصرف المرتبط بالمفردات وجزورها والنحو الذي يمثل أساس الجملة فيها … كل ذلك مما يمزها عن باقي اللغات. لذلك تُصنّف اللّغة العربيّة كواحدةٍ من اللّغات التي تَحتفظ بنظامٍ نحويٍّ خاصّ بها، ويُساعد في إعراب جُملها وبيان طُرق كتابتها. | ||
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Size of required cover | 2380 chars × 8 = 19,040 pixels will be changed Image 150 × 130 = 19,500 Pixels with three layers for RGB | ||
Cover Image | Image after Hiding |
Correlation | MSE | BER |
---|---|---|
0.994 | 0.005 | 0.002 |
# | Description | Size (Characters) | Number of Hamzas | Number of Diacritics | Secret msg Size (Bits) | Scenario 1 No. Changes | Scenario 2 No. Changes |
---|---|---|---|---|---|---|---|
T1 | Small Text without Diacritics | 120 | 20 | 0 | 10 | 4 | 10 |
T2 | Small Text with some Random Diacritics | 719 | 17 | 21 | 10 | 5 | 11 |
T3 | Medium Size text | 2500 | 59 | 1200 | 50 | 19 | 30 |
T4 | relatively long | 15,000 | 310 | 7000 | 200 | 56 | 123 |
Reference # | Approach Used | Imperceptibility | Capacity | Robustness | Security |
---|---|---|---|---|---|
[17] | Hybrid | high | high | high | high |
[29] | Kashida | unknown | high | unknown | unknown |
[32] | Diacritics | unknown | high | unknown | unknown |
[54] | Kashida | unknown | high | unknown | unknown |
[30] | Hybrid | high | unknown | unknown | unknown |
[31] | Kashida | unknown | high | unknown | high |
[33] | Kashida | unknown | high | unknown | unknown |
[34] | Kashida | unknown | high | unknown | unknown |
[35] | Kashida and Unicode | unknown | unknown | unknown | unknown |
[36] | Kashida | unknown | unknown | unknown | unknown |
[37] | shape | unknown | high | unknown | unknown |
[55] | Kashida | unknown | high | unknown | unknown |
[38] | Unicode | unknown | high | unknown | unknown |
[39] | Unicode | unknown | high | unknown | unknown |
[40] | Unicode | unknown | high | unknown | unknown |
[41] | Unicode | unknown | high | unknown | unknown |
[42] | Unicode | unknown | unknown | unknown | unknown |
[43] | Unicode | high | high | unknown | |
[44] | Diacritics | unknown | high | unknown | unknown |
[45] | Diacritics | unknown | high | unknown | unknown |
[56] | Diacritics | unknown | high | unknown | unknown |
[46] | Diacritics | unknown | high | unknown | unknown |
[47] | Diacritics | unknown | high | unknown | unknown |
[48] | Diacritics | Low | high | unknown | unknown |
[4] | Diacritics | unknown | high | high | high |
our approach | Diacritics and Hamzas | high | high | high | high |
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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Alqahtany, S.S.; Alkhodre, A.B.; Al Abdulwahid, A.; Alohaly, M. A Dynamic Multi-Layer Steganography Approach Based on Arabic Letters’ Diacritics and Image Layers. Appl. Sci. 2023, 13, 7294. https://doi.org/10.3390/app13127294
Alqahtany SS, Alkhodre AB, Al Abdulwahid A, Alohaly M. A Dynamic Multi-Layer Steganography Approach Based on Arabic Letters’ Diacritics and Image Layers. Applied Sciences. 2023; 13(12):7294. https://doi.org/10.3390/app13127294
Chicago/Turabian StyleAlqahtany, Saad Said, Ahmad B. Alkhodre, Abdulwahid Al Abdulwahid, and Manar Alohaly. 2023. "A Dynamic Multi-Layer Steganography Approach Based on Arabic Letters’ Diacritics and Image Layers" Applied Sciences 13, no. 12: 7294. https://doi.org/10.3390/app13127294
APA StyleAlqahtany, S. S., Alkhodre, A. B., Al Abdulwahid, A., & Alohaly, M. (2023). A Dynamic Multi-Layer Steganography Approach Based on Arabic Letters’ Diacritics and Image Layers. Applied Sciences, 13(12), 7294. https://doi.org/10.3390/app13127294