Designing chaotic systems with specific features is a hot topic in nonlinear dynamics. In this study, a novel chaotic system is presented with a unique feature of crossing inside and outside of a cylinder repeatedly. This new system is thoroughly analyzed by the help of the bifurcation diagram, Lyapunov exponents’ spectrum, and entropy measurement. Bifurcation analysis of the proposed system with two initiation methods reveals its multistability. As an engineering application, the system’s efficiency is tested in image encryption. The complexity of the chaotic attractor of the proposed system makes it a proper choice for encryption. States of the chaotic attractor are used to shuffle the rows and columns of the image, and then the shuffled image is XORed with the states of chaotic attractor. The unpredictability of the chaotic attractor makes the encryption method very safe. The performance of the encryption method is analyzed using the histogram, correlation coefficient, Shannon entropy, and encryption quality. The results show that the encryption method using the proposed chaotic system has reliable performance.

<p>The emergence of the Internet of Things (IOT) as a result of the development of the communications system has made the study of cyber security more important. Day after day, attacks evolve and new attacks are emerged. Hence, network anomaly-based intrusion detection system is become very important, which plays an important role in protecting the network through early detection of attacks. Because of the development in  machine learning and the emergence of deep learning field,  and its ability to extract high-level features with high accuracy, made these systems involved to be worked with  real network traffic CSE-CIC-IDS2018 with a wide range of intrusions and normal behavior is an ideal way for testing and evaluation . In this paper , we  test and evaluate our  deep model (DNN) which achieved good detection accuracy about  90% .</p>

<span lang="EN-US">In the recent years, an increasing demand for securing visual resource-constrained devices become a challenging problem due to the characteristics of these devices. Visual resource-constrained devices are suffered from limited storage space and lower power for computation such as wireless sensors, internet protocol (IP) camera and smart cards. Consequently, to support and preserve the video privacy in video surveillance system, lightweight security methods are required instead of the existing traditional encryption methods. In this paper, a new light weight stream cipher method is presented and investigated for video encryption based on hybrid chaotic map and ChaCha20 algorithm. Two chaotic maps are employed for keys generation process in order to achieve permutation and encryption tasks, respectively. The frames sequences are encrypted-decrypted based on symmetric scheme with assist of ChaCha20 algorithm. The proposed lightweight stream cipher method has been tested on several video samples to confirm suitability and validation in term of encryption–decryption procedures. The performance evaluation metrics include visual test, histogram analysis, information entropy, correlation analysis and differential analysis. From the experimental results, the proposed lightweight encryption method exhibited a higher security with lower computation time compared with state-of-the-art encryption methods.</span>

One of the fastest-growing problems with a high impact on the financial sector is financial fraud. Recently, data mining has been identified as one of the effective ways of detecting fraudulent credit card transactions. As a data mining problem, the detection of fraudulent credit card transaction is a challenging task due to the following reasons: (i) The frequent changes in the patterns of normal and fraudulent activities and (ii) the high level of skewness related with credit card fraud datasets. The aim of this article is to review the existing techniques for fraudulent transactions detection in credit cards, with more focus on the techniques that are Machine Learning (ML) based and nature inspired-based. The recent trend in the detection of credit card fraud was also presented in this article. Furthermore, the limitations and usefulness of the existing techniques for fraudulent transaction detection in credit cards were also outlined. The necessary fundamental information for further studies in this area was also provided. This review will also guide individuals and financial institutions seeking for effective techniques for credit card fraud detection, especially those that are based on ML and nature-inspired algorithms.

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IoT is one of the most popular technologies in recent years due to the interconnection of various infrastructures, physical devices, and software. To guarantee the security of Internet of Things (IoT) pervasiveness, lightweight cryptographic solutions are needed and this requires lightweight cryptographic primitives. The choice of S-box in light block ciphers plays an important role in characterizing the security-performance trade-off. The choice of the 4 × 4 S-box for the lightweight constructions results in compact hardware, speeding up the computational capability of the security algorithm unlike the 8 × 8 S-box. This work presents efficient algebraic S-boxes for a fast image cryptosystem based on a strong nonlinear function which is expanded by a biological technique depending on DNA. The robustness of the proposed S-boxes is analysed and tested against various standard attack criteria such as interpolation attacks, avalanche effect, and nonlinearity. The great advantage of introducing S-boxes is that its DSAC is the ideal value which is equal to zero. Also, other tests executed on these S-boxes guaranteed its robustness and excellent security performance. Moreover, the experiments are applied with full description in two different modes; RGB and gray images. The results of all tests proved to have fast and strong effective S-boxes.

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Block encryption algorithms rely on the two most important features of their complexity and ease of use to support security requirements (confidentiality, data integrity, and non-repudiation) to prevent unauthorized users from entering the system and tampering with centralized data, disrupting it or disclosing it. The data encryption and decryption process is done using the (Serpent) algorithm, which is one of the most important of these operations. AES Algorithm Proposals. In this paper, a new proposal is presented to improve and support the confidentiality of data while adhering to the external structure of the standard algorithm, relying on designing a new approach to the key generation function because the sobriety of block cipher relies on the use of a strong and unique key. Where several functions were used (Gost external structure) with a combination of (Shift <<<), (AES -Key Schedule), (MD5)). The results of the proposed method were examined using statistical measures, yielding good results, and overcoming the weakness of the key generation function of the original algorithm, in addition to enhancing the most important cryptographic features “confusion”, “diffusion” and “increased randomness”.