PRIVACY PROTECTION OF USER BROWSING DETAILS FOR SECURE WEB SEARCH AND UNSAFE URL DETECTION
Abstract:
Malicious URL (or) malicious website is a common and serious threat to cyber security. Naturally, search engine becomes the backbone of information management. Nevertheless, the flooding of large number of malicious websites on search engine has posed tremendous threat to our users. Most of exiting systems to detect malicious websites focus on specific attack. At the same time, available browser extensions based on blacklist are powerless to countless websites. Therefore, it is essential that any data leaving the client side should be effectively masked such that the server cannot interpret any valuable information from the masked data. Here propose the first PPSB service. It provides strong security guarantees that are missing in existing SB services. In particular, it inherits the capability of detecting unsafe URLs, while at the same time protects both the users privacy (browsing history) and blacklist provider’s proprietary assets (the list of unsafe URLs). In this work, proposed a model which encrypts the users sensitive data to prevent privacy from both outside analysts and service provider. Also, completely supports selective aggregate functions for online user behavior analysis and guaranteeing differential privacy. Homomorphic RSA algorithm is used for encrypting users online behavior data. Implementation is done and its performances are evaluated based on a real time behavior set
Frontend:
DOTNET
Backend:
SQL SERVER
Area:
APPLICATION PROJECT
Domain:
WEB CROWLING