Abstract

This study came to clarify the redemption in terms of being a method and a subject of knowledge that has its causes, controls, etiquette and scientific implications for Muslim scholars.

The science of redemption has a historical extension, starting from the era of the Companions - may God be pleased with them - and through the stages of codification and classification of works in an effort to document it and diversify its methods at the inductive, analytical, critical and argumentative levels, and to determine its causes and from the completion of the research conclude it with evidence of its scientific effects because it is a science that enriched the Islamic library in general, and hadith in particular.

In the Name of God, the Most Gracious, the Most Merciful

    Praise be to God, who has revealed the book, in which there are clear verses, insight and remembrance for the first people, and he promised those who learned it and did it with great rewards, and prayers and peace be upon those who pronounced the right and separated the speech, and on his family and companions the best of family and companions, and who followed them and guided them to the day of Moab .... ..
     And yet: If we ponder a brief period and look at our course at a glance, we will find that those who lead us are the prophets, and those who guide us are the guardians, and those who protect us are the martyrs, an

Medium Access Control (MAC) spoofing attacks relate to an attacker altering the manufacturer assigned MAC address to any other value. MAC spoofing attacks in Wireless Fidelity (WiFi) network are simple because of the ease of access to the tools of the MAC fraud on the Internet like MAC Makeup, and in addition to that the MAC address can be changed manually without software. MAC spoofing attacks are considered one of the most intensive attacks in the WiFi network; as result for that, many MAC spoofing detection systems were built, each of which comes with its strength and weak points. This paper logically identifies and recognizes the weak points
and masquerading paths that penetrate the up-to-date existing detection systems. Then the

Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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