Secure Fuzzy Keyword Search in Cloud Computing using Levenshtein Distance and Cryptographic Indexing

Growing usage of the cloud for computing, the necessity for safe and security storage and retrieval of information procedures has become important. This study provides a novel way to tackle the difficulty of searching across encrypted information in the cloud with supporting an inherent fuzzy in queries made by users. The purpose is to allow users to execute searches for keywords on their secure data saved in the cloud while maintaining the secrecy of the data. The approach we propose uses cryptographic methods, notably to secure the information before transferring it to the service. To support fuzzy searches for keywords, we apply approaches such as secure indexing building and similarity rating. This enables users to receive useful data regardless of whether their search request includes errors in spelling, typos, or small changes in the terms. The system structure makes sure a cloud server stays clueless to the details of the encrypted information and the queries used for searching. In addition, we incorporate safety measures to defend against illegal access and to preserve integrity of data throughout the searching process. Thorough tests and experiments, we show the speed as well as effectiveness of our strategy in the areas of search performance, processing overhead, and speed of response, not just enhancing the security of data provided by users but additionally provides an efficient method for safe and flexible retrieval of data in cloud-based systems of storage.