Global Fortification - Unifying Global DDoS Defense

Financial sector is enduring the painful effects of millions of dollars spent each month to combat dangerous DDoS attacks on bank services. Sometimes these attackers cloud the websites of banks to such an extent that critical services have to be halted, resulting in huge losses and reputational damage to the Company (Aljuhani, 2021). In this work, we demonstrate an artificial intelligence-based approach that detects and counteracts DDoS attacks aimed specifically at bank websites. Ensuring a high level of service for DDoS – attacked websites, this system helps to reduce financial loss due to service downtimes and as well as excessive transaction outages for clients. Furthermore, this model restricts aggressors, and implements a level of interbank information exchange regarding actual attacks. This research proposes a system for DDoS attack prevention that minimizes economic damage through the use of machine learning, which can improve the overall performance of any financial institution cybersecurity efforts. Additionally, this system integrates real – time navigation with historical data of DDoS attacks, which gives ‘forward looking’ capabilities in threat detection. It is important to note that a sophisticated anomaly detection system enables the proposed solution to significantly outperform standard models by disabling meaningful traffic while launching attacks from spurious IP addresses. This study also confirms deliberative modelled trials aimed at showing that the system is capable of greatly reducing the severity of DDoS attacks. In addition, the implemented solution provides a feasible and easily extensible approach that can easily be incorporated in the current bank’s infrastructure. The research also speaks of the possibility of crowd-sourced threat intelligence, where banks would share anonymized data related to attacks for better security.