Author: Dr.Samer Saeed Issa

Abstract Image encryption technique has emerged as a remarkable solution to shield the image against adversaries. Despite much advancement, a robust image encryption system is needed to achieve excellent encryption quality. Therefore, a highly-secured encryption algorithm needs impressive random key with excellent expansion method, small initial size and regeneratable capabilities, improved confusion and diffusion techniques. To achieve these goals a method for image encryption containing three major phases was developed. Firstly, an encryption and decryption key were generated and expanded with high level of randomness via Knight Tour (KT) algorithm with small initial size. Secondly, a new method of confusion was developed using switching technique and Discrete Diagonal-SCAN (DD-SCAN) approach for enhancing the level of pixel dispersion. Finally, an innovative method of diffusion was introduced to change the image pixels’ value using bit wise operator and pixel circular shifting method. These involved steps such as generating a Ginger bread man image using the initial key, applying Arnold Cat Map (ACM) transform to dissolve flat regions in the ginger bread man image, and performing a bit-wise operation between the outcome from ACM transform, using results from DD-SCAN method, and utilizing the pixels circular shifting based on the generated key. The encryption key was proven to withstand against several types of attacks and tested using National Institute of Standards and Technology (NIST) randomness test. Thus, the pixel’s value was altered and the cipher image was produced. The performance of the scheme was validated against forty-four images acquired from Signal and Image Processing Institute (SIPI) for standard image dataset. Shortly, the proposed image encryption scheme has been affirmed to be a superior image encryption scheme development. Keywords Image Encryption, Key Expansion, Confusion and Diffusion, Discrete Diagonal Scan, NIST in the IEEE sponsored Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT 2023)  

ABSTRACT One of the most pressing issues in wireless sensor networks (WSNs) is energy efficiency. Sensor nodes (SNs) are used by WSNs to gather and send data. The techniques of cluster-based hierarchical routing significantly considered for lowering WSN’s energy consumption. Because SNs are battery-powered, face significant energy constraints, and face problems in an energy-efficient protocol designing. Clustering algorithms drastically reduce each SNs energy consumption. A low-energy adaptive clustering hierarchy (LEACH) considered promising for application-specifically protocol architecture for WSNs. To extend the network’s lifetime, the SNs must save energy as much as feasible. The proposed developed cluster-based loadbalanced protocol (DCLP) considers for the number of ideal cluster heads (CHs) and prevents nodes nearer base stations (BSs) from joining the cluster realization for accomplishing sufficient performances regarding the reduction of sensor consumed energy. The analysis and comparison in MATLAB to LEACH, a well-known cluster-based protocol, and its modified variant distributed energy efficient clustering (DEEC). The simulation results demonstrate that network performance, energy usage, and network longevity have all improved significantly. It also demonstrates that employing cluster-based routing protocols may successfully reduce sensor network energy consumption while increasing the quantity of network data transfer, hence achieving the goal of extending network lifetime. Keywords: Cluster-based routing DCLP protocol Energy-efficient protocol LEACH protocol WSN DOI: https://beei.org/index.php/EEI/article/view/4226

Abstract: The detection rate of network intrusion detection systems mainly depends on relevant features; however, the selection of attributes or features is considered an issue in NP-hard problems. It is an important step in machine learning and pattern recognition. The major aim of feature selection is to determine the feature subset from the current/existing features that will enhance the learning performance of the algorithms, in terms of accuracy and learning time. This paper proposes a new hybrid filter-wrapper feature selection method that can be used in classification problems. The information gain ratio algorithm (GR) represents the filter feature selection approach, and the black hole algorithm (BHA) represents the wrapper feature selection approach. The comparative analysis of network intrusion detection methods focuses on accuracy and false positive rate. GBA shines with exceptional results: achieving 96.96% accuracy and a mere 0.89% false positive rate. This success can be traced to GBA’s improved initialization via the GR technique, which effectively removes irrelevant features. By assigning these features almost zero weights, GBA hones its ability to accurately spot intrusions while drastically reducing false alarms. These standout outcomes underline GBA’s superiority over other methods, showcasing its potential as a reliable solution for bolstering network security.  Keywords: Information security, Intrusion detection systems, Optimization, Feature selection, Black hole algorithm. Article: https://inass.org/wp-content/uploads/2023/07/2023123122-2.pdf

Abstract: This paper introduces a novel approach for generating strong substitution boxes (S-Boxes) using the black hole algorithm (BHA) integrated with Arnold chaotic map (ACM) and Henon chaotic map (HCM). The ACM is employed for enhanced initialization of the BHA, while the HCM is utilized for generating new stars during the searching process. The proposed algorithm, named BH-SBOX, aims to enhance the nonlinearity and cryptographic properties of the generated S-Boxes. Experimental evaluations further demonstrate that the BH-SBOX algorithm produces S-Boxes with excellent nonlinearity, strict avalanche criteria, bit independence criteria, differential uniformity, and the maximum expected linear probability. The proposed method demonstrated a high nonlinearity property, achieving a value of 108.25, which is considered successful and effective. This exceptional nonlinearity can be attributed to the utilization of the Henon map, which enables good exploration of the solution space during the search process. The chaotic and unpredictable nature of the Henon map contributes significantly to the algorithm’s ability to discover S-Boxes with enhanced nonlinearity and robust cryptographic characteristics. The average bit independence criteria (BIC) and strict avalanche criteria (SAC) were found to be 102.85 and 0.50392, respectively. These results indicate that the proposed method successfully generated S-boxes with strong cryptographic properties, ensuring robustness and resistance against various attacks. Keywords: Cryptography, Operational researches, Optimization, S-box, Chaotic map, Black hole algorithm. Article: https://inass.org/wp-content/uploads/2023/07/2023123121-2.pdf

ABSTRACT Wireless sensor networks (WSNs) has a major designing feature representing by energy. Specifically, the sensor nodes have limited battery energy and are deployed remote from base station (BS); therefore, the actual enhancement dealing with energy turns into the Clustering routing protocols fundamentals which concerned in network lifetime improvement. Though, unexpected and energy insensible of the clusters head (CH) selection is not the best of WSN for greatly lowering lifetime network. A presentation article of an WSNs incoming routing approach using a mix of the fuzzy approach besides hybrid energy-efficient distributing (HEED) algorithm for increasing the lifetime and node’s energy. The FLH-P proposal algorithm is split into two parts. The stable election protocol HEED approach is used to arrange WSNs into clusters. Then, using a combination of fuzzy inference and the low energy adaptive clustering hierarchy (LEACH) algorithm, metrics like residual energy, minimal hops, with node traffic counts are taken into account. A comparison of FLH-P proposal algorithm with LEACH algorithm, fuzzy approach, and HEED utilizing identical guiding standards was used for demonstrating the performance of the suggested technique from where corresponding consumed energy as well as lifetime maximization. The suggested routing strategy considerably increases the network lifetime and transmitted packet throughput, according to simulation findings. Keywords: Balancing consumed energy Energy-efficient clustering FLH-P proposal algorithm Network lifetime Wireless sensor networks DOI: https://ijeecs.iaescore.com/index.php/IJEECS/article/view/29251

ABSTRACT Nowadays, secure transmission massive volumes of medical data (such as COVID-19 data) are crucial but yet difficult in communication between hospitals. The confidentiality and integrity are two concerning challenges must be addressing to healthcare data. Also, the data availability challenge that related to network fail which may reason concerns to the arrival the COVID-19 data. The second challenge solved with the different tools such as virtual privet network (VPN) or blockchain technology. Towards overcoming the aforementioned for first challenges, a new scheme based on crypto steganography is proposed to secure updating (COVID-19) data. Three main contributions have been consisted within this study. The first contribution is responsible to encrypt the COVID-19 data prior to the embedding process, called hybrid cryptography (HC). The second contribution is related with the security in random blocks and pixels selection in hosting image. Three iterations of the Hénon Map function used with this contribution. The last contribution called inversing method which used with embedding process. Three important measurements were used the peak signal-to-noise ratio (PSNR), the Histogram analysis and structural similarity index measure (SSIM). Based on the findings, the present scheme gives evidence to increase capacity, imperceptibility, and security to ovoid the existing methods problem.  Keywords: Crypto-steganography Hybrid cryptography Inversing method Random blocks Virtual privet network DOI: https://ijeecs.iaescore.com/index.php/IJEECS/article/view/29231