The  adopted method in the teaching of history is conservation and indoctrination in all grades, and this will lead to a lack of students interact with teachers in the course of the lesson, and poor use of teachers to questions that raise students' thinking during the lesson, which leads to a lack of interest in the topic of the lesson and wasting opportunities contribution making it the teacher at the center of the educational process, and to provide arrogating the researcher to contribute to teaching style with the belief that the use of this method of teaching could lead to overcome the difficulties and problems faced by the teaching material.

And there are educational complexes integrated approac

Nowadays, information systems constitute a crucial part of organizations; by losing security, these organizations will lose plenty of competitive advantages as well. The core point of information security (InfoSecu) is risk management. There are a great deal of research works and standards in security risk management (ISRM) including NIST 800-30 and ISO/IEC 27005. However, only few works of research focus on InfoSecu risk reduction, while the standards explain general principles and guidelines. They do not provide any implementation details regarding ISRM; as such reducing the InfoSecu risks in uncertain environments is painstaking. Thus, this paper applied a genetic algorithm (GA) for InfoSecu risk reduction in uncertainty. Finally, the ef

Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

This paper introduces an innovative method for image encryption called "Two-Fold Cryptography," which leverages the Henon map in a dual-layer encryption framework. By applying two distinct encryption processes, this approach offers enhanced security for images. Key parameters generated by the Henon map dynamically shape both stages of encryption, creating a sophisticated and robust security system. The findings reveal that Two-Fold Cryptography provides a notable improvement in image protection, outperforming traditional single-layer encryption techniques.

Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

The Diffie-Hellman is a key exchange protocol to provide a way to transfer shared secret keys between two parties, although those parties might never have communicated together. This paper suggested a new way to transfer keys through public or non-secure channels depending on the sent video files over the channel and then extract keys. The proposed method of key generation depends on the video file content by using the entropy value of the video frames. The proposed system solves the weaknesses in the Diffie-Hellman key exchange algorithm, which is MIMA (Man-in-the-Middle attack) and DLA( Discrete logarithm attack). When the method used high definition videos with a vast amount of data, the keys generated with a large number up to 5

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Wireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB8

Objective: To know the recent shifts in the decision-making process and theories and stages, techniques and systems affecting it.
      The need for research coming  because of the problems that accompany the decision as a result of the failure Sometimes, poor visualization or the narrow perspective of decision-making than miss the opportunity to choose alternatives or options of the most effective and appropriate to solve a problem.
      And has received exceptional decision-making process in administrative studies and research to enable the organization to continue its activities and its high efficiency, especially successful that the decision depends on the future,