Efficiently Listing URLs from Active Hidden Servers in the Onion Routing Network

The Onion Routing (Tor) network has created to allow manipulators to peruse the internet anonymously. It is renowned for its strong anonymity and privacy features, which protect against various agents attempting to monitor client activities or track their browsing habits. Despite the anonymity Tor provides, Onion URLs (Uniform Resource Locator) are generated based on cryptographic keys, making them challenging to discover or censor the active hidden services. The primary objective is to enhance privacy and security on the internet by providing anonymity to users. To create an efficient online environment, allowing users to access information and communicate without the fear of surveillance or censorship. Machine Learning (ML) algorithms used to adaptively manage data traffic, ensuring that it aligns with network demands. The improvised crawling algorithm improving the by frequent IP address modification in addition to that onion routing ensuring that users access hidden services securely while maintaining the principles of anonymity and privacy inherent in the Tor network. The latency of the network is compared with different traffic requests, from that the proposed system ToR-ML outperforms 45% more when comparing with the existing ToR network system.