Insecure Url Detection And Privacy Protection Of Users Browsing Data For Secure Web Search Using Homomorphic Rsa Algorithm

Abstract

Malicious URL (or) malicious website is a common and serious threat to cyber security. Naturally, search engine becomes the backbone of information management. However, the flood of a large number of malicious websites on the search engine posed a major threat to our users. Most of the exiting frameworks for detecting malicious websites concentrate on common attacks. At the same time, usable blacklist-based browser extensions are powerless to multiple websites. It is therefore important that any data entering the client side should be effectively masked in such a way that the server cannot interpret any useful information from the masked data. Here you suggest the first PPSB operation. It offers good security protections that are lacking from current SB services. In particular, it inherits the ability to detect unsafe URLs while at the same time protecting both the privacy of the user (browsing history) and the proprietary assets of the blacklist provider (a list of unsafe URLs). In this study, it proposed a model that encrypts consumer sensitive data in order to prevent the privacy of both outside observers and service providers. This also fully supports specific aggregate functions for online user experience analysis and guarantees differential privacy. Homomorphic RSA algorithm is used to encrypt the online activity data of users. Implementation is carried out and its output is measured on the basis of a set of real-time behaviors.