Defensive Auto-Updatable and Adaptable Bot Recommender System (DAABRS): A New Architecture Approach in Cloud Computing Systems

Cloud server data security makes extensive use of data centers and instantly accessible edge systems for possible transactions involving sizable and confidential data. These Edge Systems are chosen for rental based on their usefulness in situations where new privacy and security difficulties must be overcome. The use of Edge Systems is subject to dynamic mobility, which increases the danger of attacking threats. With this suggested approach, the Defensive Auto-updatable and Adaptable Bot Recommender approach (DAABRS) is used by the Cloud Center to identify the safeguarded Edge System. Cloud Data Centers with Edge Systems contain a variety of users and environments, making it simple for attackers to enter anonymously and compromise Edge System privacy. The most effective security measure against increasing risks and assaults for Edge Systems that rent more cloud storage is to use Stealth Mode Bots inside of data segments. In addition to anticipating and averting data breaches in server partitioning, tenant systems, edge systems, and containers by integrating stealth mode bots into each. Suggested use cases: Tenants, Edge Systems, or Containers for effective security-enhanced Stealth Mode Bots that are activated when a particular data segment is unplugged. Updatable and adaptive bots are used in the suggested strategy to counter Edge strategy assaults. Additionally, it uses Stealth Mode Bots to stop heavily attacked Data Containers, and machine learning will be used to update specifications to identify and prevent further assaults.