The security of data collected and processed in the cloud is determined not only by the structure of the cloud itself, but by all aspects related to sending data to the cloud, archiving, indexing information and analyzing data collected in the cloud, including the instruments used to secure data transfer, and system security and applications running on platforms creating so-called cloud computing. Examples of large data sets collected and processed in database systems operating in cloud computing technology are the data sets used in Big Data databases used by Google applications available for Internet users and data on users of social media portals, created and developed by internet technology companies operating these social portals the media. Security of transfer, archiving and processing of data collected in this type of Big Data database systems located in the so-called Cloud computing is a priority for technology companies that collect these data resources.
Human error. According to Jay Heiser, research vice president at Gartner, “Through 2020, 95% of cloud security failures will be the customer’s fault.”, Data loss with no backup. An accident or catastrophe can lead to the permanent loss of customer data unless there are measures in place to back up that data.Insider threats. A recent research report noted, “53% of organizations surveyed confirmed insider attacks against their organization.”DDoS attacks. Distributed denial-of-service attacks pose significant risks to cloud customers and providers, including lengthy service outages, reputational damage, and exposure of customer data.Insecure APIs. As the public “front door” to your application, an API is likely to be the initial entry point for attackers. Use pen testing to uncover security weaknesses in the APIs you use.Exploits. The multitenancy nature of the cloud (where customers share computing resources) means shared memory and resources may create new attack surfaces for malicious actors,