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Covid-19 is an infectious disease caused by the SARS-CoV-2 virus and which is considered today as a global health emergency. Long before this pandemic, several others such as the plague of Athens, the plague of Antonine, the black plague, the Spanish flu, cholera, the Asian flu, AIDS raged, with consequences as fatal, even more serious than covid-19. The emergence of AI over the past ten years has brought it to the forefront of the response to this disease. The objective of this work is to present the significant contribution of AI in the fight against the new coronavirus, comparing it to previous large pandemics. A preliminary search of information related to past pandemics and covid-19 has been carried out. Next, the contribution of AI following the WHO framework for combating pandemics was presented. Finally, the discussion part resulted in the conclusion that if AI had already been fundamentally implemented during the time of the other major pandemics, the damage to human losses would have been less.

Services are usually left configured by default and therefore subjects to vulnerabilities because they are not security enforced. Web services are so popular that they are targets of attacks to intrusions related to vulnerabilities discovered by attackers. This work proposes an architecture for patching Web service misconfigurations related to existing vulnerabilities. The approach underlying this architecture first retrieves and structures anti-vulnerability measures published by the official service manufacturers. Second, it evaluates the risk level using Common Vulnerability Scoring System (CVSS) on the current state of configurations. The proposed approach has been applied on Apache server on four vulnerabilities: version discovery, XSS, SQL injection and deny of service. Experimental results on a vulnerable environment demonstrate that the proposed approach considerably reduces vulnerabilities compared to similar solutions.