The importance of image security in the field of medical imaging is challenging. Several research works have been conducted to secure medical healthcare images. Encryption, not risking loss of data, ...is the right solution for image confidentiality. Due to data size limitations, redundancy, and capacity, traditional encryption techniques cannot be applied directly to e-health data, especially when patient data are transferred over the open channels. Therefore, patients may lose the privacy of data contents since images are different from the text because of their two particular factors of loss of data and confidentiality. Researchers have identified such security threats and have proposed several image encryption techniques to mitigate the security problem. However, the study has found that the existing proposed techniques still face application-specific several security problems. Therefore, this paper presents an efficient, lightweight encryption algorithm to develop a secure image encryption technique for the healthcare industry. The proposed lightweight encryption technique employs two permutation techniques to secure medical images. The proposed technique is analyzed, evaluated, and then compared to conventionally encrypted ones in security and execution time. Numerous test images have been used to determine the performance of the proposed algorithm. Several experiments show that the proposed algorithm for image cryptosystems provides better efficiency than conventional techniques.
Steganography algorithms hide the secret message in the cover image and provide imperceptibility to the attacker. The Least Significant Bit (LSB) algorithm is the preferred data hiding method. In ...this method, the least significant bit of the cover image pixel is substituted with the secret data bit. However, this method provides high variability if k-LSB bits of the cover image is replaced with secret data bit. To reduce the variability, various optimization algorithms are deployed in image steganography. These algorithms search the optimal pixels in the cover image, and data hiding is performed using the k-bits LSB method. Several iterations of optimization algorithms have increased the time complexity upon achieving this goal. Therefore, in this paper, a data hiding approach is designed based on the flipping approach that reduces variability and provides lesser time complexity. In the proposed method, initially, data hiding is performed using the k-bit LSB method in the cover image, and stego image is obtained. After that, the absolute difference between the cover and stego image is determined and compared with the threshold value. If the absolute difference is higher than the threshold value, then the adjacent bit of the k-bit LSB method is flipped. This process reduces the variability because flipping the adjacent bit will make the pixel value of the stego image closer to the cover image. The simulation evaluates using various performance metrics upon testing on standard dataset images. The simulation results show that the proposed method provides lesser variability, good visual quality, lesser time complexity than Genetic and Bayesian Optimization algorithms and the existing flip method.
Reversible data hiding (RDH) techniques recover the original cover image after data extraction. Thus, they have gained popularity in e-healthcare, law forensics, and military applications. However, ...histogram shifting using a reversible data embedding technique suffers from low embedding capacity and high variability. This work proposes a technique in which the distribution obtained from the cover image determines the pixels that attain a peak or zero distribution. Afterward, adjacent histogram bins of the peak point are shifted, and data embedding is performed using the least significant bit (LSB) technique in the peak pixels. Furthermore, the robustness and embedding capacity are improved using the proposed dynamic block-wise reversible embedding strategy. Besides, the secret data are encrypted before embedding to further strengthen security. The experimental evaluation suggests that the proposed work attains superior stego images with a peak signal-to-noise ratio (PSNR) of more than 58 dB for 0.9 bits per pixel (BPP). Additionally, the results of the two-sample t-test and the Kolmogorov–Smirnov test reveal that the proposed work is resistant to attacks.
Emergence of Internet of Things (IoT) and modern digital applications such as digital financial services and deliveries make it easy to reproduce and re-distribute digital contents thus give room to ...so many copyright violations of illegal use of contents that need to be resolved. Researcher have been presenting the watermarking algorithms to prevent these illicit activities to a document before distribution. However, several issues have been identified for the digital transactions in the IoT. Thus, this research proposes a new text document image watermarking algorithm which emphasizes on two most important measures, visual quality, and robustness. To boost these measures, third least significant bit has been used for insertion. In addition, to further strengthen the technique, the Pascal Triangle is applied to determine the best position for embedding. Experimental results on the standard dataset have revealed that the proposed watermarking has achieved very encouraging results with PSNR and NCC averaged 54.95db and 0.98, respectively.
Data security is one of the critical challenges for digital information. The existing steganography algorithms hide confidential data in the cover media to preserve the presence of hidden data. One ...type of steganography algorithm is a puzzle-based algorithm such as sudoku, magic cube, and basic nonogram puzzle. These puzzles depend on an auxiliary reference matrix for communication with the receiver. However, using a reference matrix is prone to a statistical histogram attack because image data hiding pixels are fixed. The challenging task here is to design a secured secret data technique that hides the secret data bits in the cover using a suitable puzzle without communicating the reference matrix with the receiver. This paper proposes a new Binary Nonogram Puzzle (BNP) technique. The BNP is based on two elements: searching the BNP indexes based on LSB of the cover pixel and hiding the secret data in random pixel based on the index information. The first row and column for each block are considered an index for the remaining block elements used for data hiding. We also identify the position to hide the secret data that calculates vertical and horizontal summation to indicate a suitable index with the specified rule. The effectiveness of the BNP was tested on the standard dataset images (USC-SIPI image database) and evaluated using Peak signal-to-noise ratio (PSNR) and Mean Square Error (MSE). The results showed that BNP achieves high PSNR and low MSE compared to the existing puzzles (Magic Cube and Basic Nonogram puzzle) and guarantees a better stego image quality.
Cybersecurity is important in the field of information technology. One most recent pressing issue is information security. When we think of cybersecurity, the first thing that comes to mind is ...cyber-attacks, which are on the rise, such as Ransomware. Various governments and businesses take a variety of measures to combat cybercrime. People are still concerned about ransomware, despite numerous cybersecurity precautions. In ransomware, the attacker encrypts the victim's files/data and demands payment to unlock the data. Cybersecurity is a collection of tools, regulations, security guards, security ideas, guidelines, risk management, activities, training, insurance, best practices, and technology used to secure the cyber environment, organization, and user assets. This paper analyses ransomware attacks, techniques for dealing with these attacks, and future challenges.
Optimal match in the cover media was found to be effective for accurate data hiding and improving the visual quality of steganography algorithms. Lately, several optimized steganography algorithms ...including least significant bit (LSB) match, genetic algorithm (GA), particle swarm optimization (PSO) were developed for cloud data security against possible attacks. Although these algorithms can search optimal bits match in the cover media to hide the secret data precisely with less variability, the techniques consume computational time. Therefore, this paper proposed a steganography technique which can achieve almost zero variability and very low computational time. The data hiding of secret data bits in complemented or non-complemented forms were achieved and optimized by using video steganography. Furthermore, the indexes for the complemented or non-complemented form were hidden in the covered frame. This allowed information to be conveyed efficiently to the receiver when extracting the secret messages. The performance of the proposed algorithm was assessed using various parameters such as peak signal to noise ratio (PSNR), embedding capacity, normalized cross-correlation, average difference and normalized absolute error. The Results revealed that the proposed steganography system is superior compared to the existing state of the art techniques. The developed algorithm was established to be greatly effective for video data security management in cloud computing.
In the recent few years, data communication through the Internet of Things (IoT) network is increased exponentially. However, the data is prone to several attacks on the network. The most popular ...attacks are eavesdropping, replay, man-in-the-middle attack, etc. To prevent these attacks, cryptography algorithms are used. The devices are deployed in the IoT network are resource constraint, limited memory, and low battery life. Therefore, the National Institute of Standard and Technology (NIST) recommended the lightweight cryptography algorithm to provide security in these devices. In this paper, we have reviewed the recent lightweight cryptography algorithms. Next, it defines the open research challenges and recommendations based on the literature review.
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