Cybersecurity Frameworks for Cloud-Hosted Financial Applications

Abstract

The use of cloud hosting is growing in popularity among managers. The hazards and threats are increased when the data is stored in the cloud. To optimise security and effectively manage risks, a robust security model is necessary. Cyber threats are efforts to get private information without authorisation, alter, or remove it, demand money from victims, or interfere with corporate operations. Identity theft, virus threats, online and email fraud, and bank fraud are all considered forms of cybercrime. This technique is used by both people and businesses to protect their digital systems, including data canters. Among the issues with traditional methods of network security are their incapacity to detect sophisticated and insider attacks, slow reaction times, and lack of scalability. These shortcomings show how research is needed to develop more comprehensive and effective security techniques to protect against the growing range of network threats. putting strong security measures in place to safeguard private information and guarantee business continuity. The design and optimisation of a thorough cybersecurity framework made especially for network applications are examined in this paper. The framework emphasises using best practices to safeguard applications, integrating cutting-edge security technology, and identifying and reducing security threats. This paper presents an artificial intelligence-based cyber security method for financial sector management (CS-FSM). Artificial intelligence is one of the strongest tools for mapping and preventing unforeseen hazards from consuming an organisation. The suggested method may be used to categorise and resolve cyberattack issues. Algorithms like the Enhanced Encryption Standard (EES) encrypt and decode data to guarantee the security of financial sector information. The K-Nearest Neighbour (KNN) algorithm generates predictions by learning from the training data. It is used in the banking industry to identify and thwart malware assaults. By strengthening cyber security systems' defences against cyberattacks, the suggested approach improves their performance. CS-FSM improves the ratios of attack avoidance (11.2%), risk reduction (13.2%), security of information (16.2%), scalability (17.2%), and data privacy (18.3%).