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This research focuses on creating a robust model for detecting texts produced by large language models popular in the field of natural language processing, based on the assumption that machine learning technology can detect machine learning technology. The first study explores the field of cyber security and highlights the potential risks associated with using AI-generated texts in malicious ways.

The researcher created different types of denial-of-service attacks and applied modified algorithms to the data after calculating statistical features based on time difference between payloads passing through the encrypted channel, and tested multiple types of traditional and deep learning algorithms. This is to examine their efficiency in distinguishing four types of attacks and improve detection accuracy. Inter arrival time was calculated, which is the time difference between each two successive loads.

This study deals with the use of new media by civil society organizations to achieve their communication goals with the local press. It aims to identify the reality of the use of digital media tools by the Palestinian Prisoner Club Association, and the trends in how journalists deal with new media in communicating with the club. This study used the gratifications theory and the concept of advocacy.