Optical Bit-Plane-Based 3D-JST Cryptography Algorithm With Cascaded 2D-FrFT Encryption for Efficient and Secure HEVC Communication

El‐Shafai, Walid; Almomani, Iman; Alkhayer, Aala

doi:10.1109/access.2021.3062403

Cited by 47 publications

(13 citation statements)

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“…The Laplacian operator can be represented by L ( x ( m , n )), where x ( m , n ) is the input stego or cover video frame, and ( m , n ) refers to the spatial location of the video frame pixels. This operator can be mathematically represented as in Equation ( 2 ) [ 56 ].

…”

Section: Results and Comparisonsmentioning

confidence: 99%

A Crypto-Steganography Approach for Hiding Ransomware within HEVC Streams in Android IoT Devices

Almomani

Alkhayer

El‐Shafai

2022

Sensors

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Steganography is a vital security approach that hides any secret content within ordinary data, such as multimedia. This hiding aims to achieve the confidentiality of the IoT secret data; whether it is benign or malicious (e.g., ransomware) and for defensive or offensive purposes. This paper introduces a hybrid crypto-steganography approach for ransomware hiding within high-resolution video frames. This proposed approach is based on hybridizing an AES (advanced encryption standard) algorithm and LSB (least signification bit) steganography process. Initially, AES encrypts the secret Android ransomware data, and then LSB embeds it based on random selection criteria for the cover video pixels. This research examined broad objective and subjective quality assessment metrics to evaluate the performance of the proposed hybrid approach. We used different sizes of ransomware samples and different resolutions of HEVC (high-efficiency video coding) frames to conduct simulation experiments and comparison studies. The assessment results prove the superior efficiency of the introduced hybrid crypto-steganography approach compared to other existing steganography approaches in terms of (a) achieving the integrity of the secret ransomware data, (b) ensuring higher imperceptibility of stego video frames, (3) introducing a multi-level security approach using the AES encryption in addition to the LSB steganography, (4) performing randomness embedding based on RPS (random pixel selection) for concealing secret ransomware bits, (5) succeeding in fully extracting the ransomware data at the receiver side, (6) obtaining strong subjective and objective qualities for all tested evaluation metrics, (7) embedding different sizes of secret data at the same time within the video frame, and finally (8) passing the security scanning tests of 70 antivirus engines without detecting the existence of the embedded ransomware.

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…”

Section: Results and Comparisonsmentioning

confidence: 99%

A Crypto-Steganography Approach for Hiding Ransomware within HEVC Streams in Android IoT Devices

Almomani

Alkhayer

El‐Shafai

2022

Sensors

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“…• Laplacian Mean Square Error (LMSE) LMSE evaluation metric [36] is based on estimating the measurement of video frame edges. It is better to achieve a small LMSE value to obtain a good quality for the resulted stego video frame.…”

Section: • Maximum Difference (Md)mentioning

confidence: 99%

Novel Ransomware Hiding Model Using HEVC Steganography Approach

Almomani¹,

Alkhayer²,

El‐Shafai³

2022

Computers, Materials &Amp; Continua

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Ransomware is considered one of the most threatening cyberattacks. Existing solutions have focused mainly on discriminating ransomware by analyzing the apps themselves, but they have overlooked possible ways of hiding ransomware apps and making them difficult to be detected and then analyzed. Therefore, this paper proposes a novel ransomware hiding model by utilizing a block-based High-Efficiency Video Coding (HEVC) steganography approach. The main idea of the proposed steganography approach is the division of the secret ransomware data and cover HEVC frames into different blocks. After that, the Least Significant Bit (LSB) based Hamming Distance (HD) calculation is performed amongst the secret data's divided blocks and cover frames. Finally, the secret data bits are hidden into the marked bits of the cover HEVC frame-blocks based on the calculated HD value. The main advantage of the suggested steganography approach is the minor impact on the cover HEVC frames after embedding the ransomware while preserving the histogram attributes of the cover video frame with a high imperceptibility. This is due to the utilization of an adaptive steganography cost function during the embedding process. The proposed ransomware hiding approach was heavily examined using subjective and objective tests and applying different HEVC streams with diverse resolutions and different secret ransomware apps of various sizes. The obtained results prove the efficiency of the proposed steganography approach by achieving high capacity and successful embedding process while ensuring the hidden ransomware's undetectability within the video frames. For example, in terms of embedding quality, the proposed model achieved a high peak signal-to-noise ratio that reached 59.3 dB and a low mean-square-error of 0.07 for the examined HEVC streams. Also, out of 65 antivirus engines, no engine could detect the existence of the embedded ransomware app.

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“…Different approaches have been adopted for forgery detection, such as passive and active approaches [8][9][10]. Active forgery detection techniques work on the principles of embedding external information in the image, such as a watermark [11][12][13] or a digital signature [14][15][16]. Verification is performed through the detection of the watermark or signature.…”

Section: Related Workmentioning

confidence: 99%

“…The algorithm in [15] divides the image into a fixed number of blocks equal to 32 blocks for a row and 32 blocks for a column. For any image, the length of blocks is changed, but the number is fixed.…”

Section: Related Workmentioning

confidence: 99%

Efficient Forgery Detection Approaches for Digital Color Images

Baumy¹,

Algarni²,

Abdalla³

et al. 2022

Computers, Materials &Amp; Continua

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This paper is concerned with a vital topic in image processing: color image forgery detection. The development of computing capabilities has led to a breakthrough in hacking and forgery attacks on signal, image, and data communicated over networks. Hence, there is an urgent need for developing efficient image forgery detection algorithms. Two main types of forgery are considered in this paper: splicing and copy-move. Splicing is performed by inserting a part of an image into another image. On the other hand, copy-move forgery is performed by copying a part of the image into another position in the same image. The proposed approach for splicing detection is based on the assumption that illumination between the original and tampered images is different. To detect the difference between the original and tampered images, the homomorphic transform separates the illumination component from the reflectance component. The illumination histogram derivative is used for detecting the difference in illumination, and hence forgery detection is accomplished. Prior to performing the forgery detection process, some pre-processing techniques, including histogram equalization, histogram matching, high-pass filtering, homomorphic enhancement, and single image super-resolution, are introduced to reinforce the details and changes between the original and embedded sections. The proposed approach for copy-move forgery detection is performed with the Speeded Up Robust Features (SURF) algorithm, which extracts feature points and feature vectors. Searching for the copied partition is accomplished through matching with Euclidian distance and hierarchical clustering. In addition, some preprocessing methods are used with the SURF algorithm, such as histogram equalization and single-mage super-resolution. Simulation results proved the feasibility and the robustness of the pre-processing step in homomorphic detection and SURF detection algorithms for splicing and copy-move forgery detection, respectively.

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Optical Bit-Plane-Based 3D-JST Cryptography Algorithm With Cascaded 2D-FrFT Encryption for Efficient and Secure HEVC Communication

Cited by 47 publications

References 47 publications

A Crypto-Steganography Approach for Hiding Ransomware within HEVC Streams in Android IoT Devices

A Crypto-Steganography Approach for Hiding Ransomware within HEVC Streams in Android IoT Devices

Novel Ransomware Hiding Model Using HEVC Steganography Approach

Efficient Forgery Detection Approaches for Digital Color Images

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