Utilization of Corner Filters, AES and LSB Steganography for Secure Message Transmission

Alexan, Wassim; Elkhateeb, Abdelrahman; Mamdouh, Eyad; Al-Seba'ey, Fahd; Amr, Ziad; Khalil, Hana

doi:10.1109/icm52667.2021.9664947

Cited by 17 publications

(6 citation statements)

References 20 publications

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“…Dataset labeled to train the classifier in 80% while 20% used for testing mode. To fit parameter of (𝜃) use (11):…”

Section: Resultsmentioning

confidence: 99%

“…The watermark cannot remove information from it unless part of the image information is damaged, and this information is often. It is subject to change because it is among the least important area in the image, or the so-called LSB [11]. Among the security information that has a hidden character, including fingerprints, and Iris of our most interest in the technique of hiding information, which is the focus of our research is to include a message in the cover of the image, which is considered the main carrier in information transmission technologies.…”

Section: Steganographymentioning

confidence: 99%

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Improve steganography system using agents software based on statistical and classification technique

Halboos¹,

Al-Bakry²

2023

Bulletin EEI

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In digital communications, information security is a paramount necessity. In the hiding algorithm, there are three basic parameters: security, capacity, and imperceptibility. Therefore, there are many ways to design the steganography algorithm, such as least significant bit (LSB), discrete wave transformation (DWT), and discrete cosine transform (DCT). The aim of this paper is to improve agent software design based on a steganography system. It proposed an agent system based on a support vector machine (SVM) classifier to hide a secret message in a certain cover image. The common dataset for steganography uses 80% training and 20% testing to get accurate results. Developing an agent system depends on six statistical parameters such as energy, standard deviation, histogram, variance, mean, and entropy. This resulted in features classified by the SVM classifier to predict the best cover image to be nominated for embedding. Worthy results were obtained in terms of imperceptibility, attack, and cover image prediction by statistical issues.

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“…Dataset labeled to train the classifier in 80% while 20% used for testing mode. To fit parameter of (𝜃) use (11):…”

Section: Resultsmentioning

confidence: 99%

Section: Steganographymentioning

confidence: 99%

Improve steganography system using agents software based on statistical and classification technique

Halboos¹,

Al-Bakry²

2023

Bulletin EEI

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“…In several research works, stenography techniques are combined with other cryptography algorithms to enhance the security and privacy of hidden secret data. In [ 31 ], the authors combined cryptography and stenography techniques to obtain a high security standard. Initially, the data was encrypted using an AES algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Furthermore, the authors of [ 33 ] have also adopted the AES algorithm as a security technique to encrypt the data before hiding it with the carrier file. However, in [ 31 ], two schemes were proposed in which LSB stenography is applied along with image processing and cryptography in order to secure sensitive data. Moreover, the authors of [ 34 ] have proposed a new embedding algorithm in which they apply sequential multiples for LSB real-time data hiding algorithm.…”

Section: Literature Reviewmentioning

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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“…While some researchers have focused their efforts into advancing cryptographic algorithms [6][7][8][9], others have dedicated their efforts towards the field of steganography [10,11].…”

Section: Introductionmentioning

confidence: 99%

A 3-Layer PSN for Image Encryption Utilizing Fractional-Order Chen Hyperchaotic Map and Cryptographically-Secure PRNGs

Alexan¹,

Alexan²,

Gabr³

2023

Preprint

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Image encryption is increasingly becoming an important area of research in information security and network communications, as digital images are widely used in various applications and are vulnerable to various types of attacks. In this research work, a color image cryptosystem that is based on a 3-layer permutation-substitution network (PSN) is proposed. For every layer, an encryption key and an S-box are generated and utilized. Those are based on a four-dimensional (4D) dynamical Chen system of a fractional-order, the Mersenne Twister, OpenSLL, Rule 30 Cellular Automata and Intel’s MKL. The sequential application of Shannon’s ideas of diffusion and confusion for 3 times guarantees a total distortion of any input plain image, resulting in a totally encrypted one. Apart from the excellent and comparable performance to counterpart algorithms from the literature, showcasing resistance to visual, statistical, entropy, differential, known plaintext and brute-force attacks, the proposed image cryptosystem provides an exceptionally superior performance in 2 aspects: a vast key space of 2^1658 and an average encryption rate of 3.34 Mbps. Furthermore, the proposed image cryptosystem is shown to successfully pass all the tests of the NIST SP 800 suite.

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Utilization of Corner Filters, AES and LSB Steganography for Secure Message Transmission

Cited by 17 publications

References 20 publications

Improve steganography system using agents software based on statistical and classification technique

Improve steganography system using agents software based on statistical and classification technique

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

A 3-Layer PSN for Image Encryption Utilizing Fractional-Order Chen Hyperchaotic Map and Cryptographically-Secure PRNGs

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