Applied Cryptography and Noise Resistant Data Security

Hussain, Iqtadar; Ahmed, Fawad; Khokhar, Umar Mujahid; Anees, Amir

doi:10.1155/2018/3962821

Cited by 11 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To reduce time complexity, images can be encrypted using chaos and transformation techniques such as Discrete Cosine transform (DCT) and DWT [19][20][21][22][23][24][25][26][27][28]. In the past few years, chaos has played a vital role in image encryption due to its some unique features such as sensitivity in initial conditions, unpredictability, pseudo randomness, ergodicity, and non-deterministic behavior [29][30][31][32][33][34].…”

Section: Plos Onementioning

confidence: 99%

See 1 more Smart Citation

A lightweight noise-tolerant encryption scheme for secure communication: An unmanned aerial vehicle application

et al. 2022

View full text Add to dashboard Cite

In the modern era, researchers have focused a great deal of effort on multimedia security and fast processing to address computational processing time difficulties. Due to limited battery capacity and storage, Unmanned Aerial Vehicles (UAVs) must use energy-efficient processing. In order to overcome the vulnerability of time inefficiency and provide an appropriate degree of security for digital images, this paper proposes a new encryption system based on the bit-plane extraction method, chaos theory, and Discrete Wavelet Transform (DWT). Using confusion and diffusion processes, chaos theory is used to modify image pixels. In contrast, bit-plane extraction and DWT are employed to reduce the processing time required for encryption. Multiple cyberattack analysis, including noise and cropping attacks, are performed by adding random noise to the ciphertext image in order to determine the proposed encryption scheme’s resistance to such attacks. In addition, a variety of statistical security analyses, including entropy, contrast, energy, correlation, peak signal-to-noise ratio (PSNR), and mean square error (MSE), are performed to evaluate the security of the proposed encryption system. Moreover, a comparison is made between the statistical security analysis of the proposed encryption scheme and the existing work to demonstrate that the suggested encryption scheme is better to the existing ones.

show abstract

Section: Plos Onementioning

confidence: 99%

“…More randomness in an image results in a higher value of entropy. This relation is shown in Eq (21):…”

Section: Entropymentioning

confidence: 99%

A lightweight noise-tolerant encryption scheme for secure communication: An unmanned aerial vehicle application

et al. 2022

View full text Add to dashboard Cite

show abstract

“…One advantage of EAs is their efficiency in terms of computation time. However, insufficient encryption, as evidenced by patterns visible even after encryption, indicates a flaw in the EA [7,8]. For proper concealment and a sufficient level of encryption of textual data, conventional Data Encryption Standard (DES) and Advanced Encryption Standard (AES) are well-known techniques [9,10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Machine Learning Technique for Selecting Suitable Image Encryption Algorithms for IoT Applications

Shafique

Mehmood

Alawida

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

The Internet of Things connects billions of intelligent devices that can interact with one another without human intervention, and during communication, a large amount of data is exchanged between the devices. As a result, it is critical to secure digital data using an encryption technique that provides a suitable degree of security. Numerous existing encryption techniques do not offer sufficient security. Therefore, it is critical to figure out which encryption technique is most appropriate for a particular kind of data. When it comes to manually deciding which encryption technique to use, the process might take a long time. In this research, we present a novel technique for selecting Encryption Algorithms (EAs) based on a particular application using pattern recognition and machine learning techniques. To accomplish this goal, we also prepare a dataset. Several machine learning techniques, such as Support Vector Machines (SVMs), Linear Regression (LR), K -Nearest Neighbour (KNN), Naïve Bayes (NB), Decision Trees (DT), and Random Forests (RF), are evaluated. Based on the evaluation, the SVM has been chosen as the best option for the intended technique because its classification accuracy is 98.7%. The experimental results, including accuracy, precision, recall, and F1-score, are used to gauge the performance of the suggested technique. The proposed technique is also compared with the existing techniques to demonstrate its effectiveness.

show abstract

“…Chaotic systems are often used to generate random key streams by selecting appropriate initial conditions and state variables, which are also known as key parameters or seeds and then encrypted images can be produced by employing the generated key streams [13]. A slight change in the seed values may cause completely different key streams and thus a significant difference can occur in the output image (encrypted This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.…”

Section: Introductionmentioning

confidence: 99%

Noise-Resistant Image Encryption Scheme for Medical Images in the Chaos and Wavelet Domain

et al. 2021

View full text Add to dashboard Cite

In this paper, a noise-resistant image encryption scheme is proposed. We have used a cubic-logistic map, Discrete Wavelet Transform (DWT), and bit-plane extraction method to encrypt the medical images at the bit-level rather than pixel-level. The proposed work is divided into three sections; In the first and the last section, the image is encrypted in the spatial domain. While the middle section of the proposed algorithm is devoted to the frequency domain encryption in which DWT is incorporated. As the frequency domain encryption section is a sandwich between the two spatial domain encryption sections, we called it a "sandwich encryption." The proposed algorithm is lossless because it can decrypt the exact pixel values of an image. Along with this, we have also gauge the proposed scheme's performance using statistical analysis such as entropy, correlation, and contrast. The entropy values of the cipher images generated from the proposed encryption scheme are more remarkable than 7.99, while correlation values are very close to zero. Furthermore, the number of pixel change rate (NPCR) and unified average change intensity (UACI) for the proposed encryption scheme is higher than 99.4% and 33, respectively. We have also tested the proposed algorithm by performing attacks such as cropping and noise attacks on enciphered images, and we found that the proposed algorithm can decrypt the plaintext image with little loss of information, but the content of the original image is visible.INDEX TERMS Discrete Wavelet Transform (DWT), Chaotic map, Medical images, Bit-plane decomposition, Security analysis of medical images.

show abstract

Applied Cryptography and Noise Resistant Data Security

Cited by 11 publications

References 0 publications

A lightweight noise-tolerant encryption scheme for secure communication: An unmanned aerial vehicle application

A lightweight noise-tolerant encryption scheme for secure communication: An unmanned aerial vehicle application

A Novel Machine Learning Technique for Selecting Suitable Image Encryption Algorithms for IoT Applications

Noise-Resistant Image Encryption Scheme for Medical Images in the Chaos and Wavelet Domain

Contact Info

Product

Resources

About