Summary of the jurisprudence research

  Praise be to God, Lord of the Worlds, and prayers and peace be upon the Master of the Messengers, our master Muhammad, and upon his pure family, and his ignorant and ignorant companions, and those who followed them in goodness until the Day of Judgment.

 Then:

 The many jurisprudential aspects that the Shafi’i imams said are of great importance, because these aspects are nothing but the opinions of venerable jurists who have reached a high degree of knowledge until they have become among the owners of faces. And among them are the Shafi’i jurists, the jurists may differ among themselves, either because there is no text about their imam in a

A poetic vision appeared in the poem of Al-Abbas bin Mardas Al-Sulami. He lived in the eras of pre-Islamic times and the emergence of Islam. The focus of this research: is the study of poetic text in the pre-Islamic era and the era of early Islam. The research followed a method in treating poetic texts, as it is based on presenting poetic texts from the collection of Al-Abbas bin Mardas, explaining the features of his poetic vision, and examining all the external factors that surrounded the poet and influenced his vision and all his thoughts. The results of this research was that Al-Abbas Ibn Mardas revealed some of the positions that he found contradicted the authentic Arab value before the advent of Islam, and the poet Abbas bin Mardas tr

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a