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The study of proactive threat monitoring is a promising field of interest as it has great potential for communication network services in sectors like the commercial marketplace, government, military, and so on. From an economic, human resources, …
The study of proactive threat monitoring is a promising field of interest as it has great potential for communication network services in sectors like the commercial marketplace, government, military, and so on. From an economic, human resources, and sustainability standpoint, many enterprises and organizations are beginning to transition their network infrastructures into cloud computing environments. IT (Information Technology) solutions offered by cloud computing companies promise to be more secure than those offered by other providers. Obviously, cloud computing protects computers from physical theft, but there are other critical considerations to address as well. It is the responsibility of cloud suppliers and customers to work together to ensure the security of their data in the cloud. “Azure by Microsoft, which holds the slogan of Invent with purpose, has become one of the most famous and biggest cloud computing providers” [1]. Azure has engaged a huge number of businesses and individuals to its services over the last few years. The security-related risks of the Azure cloud computing adoption can be crucial. To address these issues, a cost-effective and efficient monitoring solution is needed. The goal of this Thesis is to build such a threat monitoring system for the reconciliation of the occurrence of the most dangerous attacks against the androids. In the Thesis, we discuss threat monitoring using the android robot as an example. This involves the use of different IoT (Internet of Things) systems as components of the robots. In order to approach the human appearance, we put our robot into a cloud wireless environment. Because cyber-attacks are becoming more sophisticated, it is more important than ever to defend enterprise wireless networks and information systems. A threat monitoring system must be able to monitor enormous amounts of data generated from networks and identify threats. There is a growing interest in cloud computing solutions, but many businesses may not be aware of wireless security dangers and their potential integration with cloud computing security for vital systems. So, we discuss the most important aspects of wireless technology and its evolution here, too. To test our proactive monitoring system against threats and vulnerabilities, we will be depending on the exploits databases (Exploit Pack, Exploit Database and Rapid7) to test it. The exploits databases are a great tool for finding potential network vulnerabilities and keeping up with existing network attacks. The findings of my thesis during test our systems claims that The average time to fix the vulnerabilities in these exploits was 500 seconds for high, about the same for medium, and 650 seconds for low severity vulnerabilities. The average time involved the collection and reverse engineering of exploits, the download, and installation of the fixes, and the rescanning of the system components. In comparison, the manual collection of the same vulnerabilities took 8 working hours. The manual installation of the patches cost another 8 working hours. So, the AI (Artificial Intelligence) supported version was better in order of magnitude. Furthermore, during the manual process, several human errors were detected (forgotten documentation, downloading the wrong version of the patch...)
