Efficient Dynamic Phishing Safeguard System Using Neural Boost Phishing Protection

The instances of privacy and security have reached the point where they cannot be ignored. There has been a rise in data breaches fraud, particularly banks, healthcare, government sectors. In today’s world, many organizations offer their specialists bug report programs that help them find flaws applications. breach on its own does not necessarily constitute threat or attack. Cyber-attacks allow cyberpunks to gain access machines networks steal financial esoteric information as result breach. this context, paper proposes an innovative approach users avoid online subterfuge by implementing Dynamic Phishing Safeguard System (DPSS) using neural boost phishing protection algorithm focuses phishing, optimizes problem breaches. safeguard utilizes 30 different features predict whether website is website. addition, uses Anti-Phishing Neural Algorithm (APNA) Boosting (APBA) generate output mapped various other components, such IP finder, geolocation, location mapper, order pinpoint vulnerable sites user can view, which makes system more secure. also offers blocker, tracker auditor give authority control system. Based results, anti-phishing achieved accuracy level 97.10%, while boosting yielded 97.82%. According evaluation dynamic systems tend perform better than models terms uniform resource locator detection security.