Ontology defines the types, properties and the interrelationships of entities that exist in a domain of discourse. The existing profile-based Personalized Web Search does not support runtime profiling. Hence to overcome the drawback in the existing system, we propose a personalized web search model for weblog dataset. The model builds a client side web assistant facilitating personalization of web search at client end. The user’s long-term dynamic profiles are stored, maintained and it is used to personalize the search request. The model uses a manually built ontology which is created by jquery, at client side to expand the query and generate clusters of similar results. The Client’s profile is stored as a an ontology tree. The MD5 algorithm is used to secure the user’s profile by encrypting. Effective personalization of information access involves two important challenges: String Similarity Match (SSM) algorithm accurately identifies the user context and organizes the information in such a way that matches the particular context. Rijndael algorithm is used to encrypt and decrypt search query and IP address to improve the quality of the search result and also to improve the security. The web search results from the existing search engine are ranked based on the client’s profile. The semantic evidence in an ontological user profile helps in the effective presentation of the most relevant results to the user.