A Privacy-Preserving Plug-and-Play Browser Integrating Edge-Based Reasoning Large Language Models with Localized Search and Secure Web Detection

Web browsers have become the primary interface for accessing online services, communication platforms, and information resources. To enhance functionality and security, many modern browsers rely on cloudbased services for search, reasoning, and threat analysis. While this approach improves performance and scalability, it requires the transfer of user queries and browsing data to remote servers, raising concerns related to privacy, data exposure, and loss of user control. This paper proposes a privacy-preserving plug-and-play browser framework designed to operate entirely within the client environment. The proposed framework integrates edge-based reasoning using lightweight large language models, localized on-device search, and browser-level secure web detection to support privacy-aware browsing. All monitoring, reasoning, and enforcement processes are performed locally on the user’s device, eliminating reliance on external services and reducing the risk of unauthorized data disclosure. The framework continuously observes browser behavior and applies adaptive privacy enforcement based on contextual execution patterns. A qualitative assessment indicates that the proposed approach can enhance user privacy while maintaining acceptable performance and usability, demonstrating that client-side intelligent browser architectures provide a viable alternative to cloud-dependent browsing models.