Text mining is the process to extract relevant information from large volume of database. Nowadays, security with text mining is contributing very important role to extract relevant information in secure and effective way on websites and social networking. In existing, there are many research work are done in terms of privacy. Here, some research article provides intrusion detection techniques, Anonymization Cryptographic, Perturbation and k-anonymity, Sanitization, Blocking-Based, space transformation, Noise Addition etc. However, these techniques have key complexities issues; accuracy problem, data classification issues and time consumption which are required to be addressed. After study of many research articles, this empirical study work is noticed that there is a need to develop some technologies to extract the relevant information from large volume of datasets in online environment with privacy and without compromising accuracy and data retrieval time in text mining. This work also plans to work efficient data visualization with filtering facilities. Finally, this survey work elaborates existing approach details along with limitation and represents the technical gap between current requirement and available technology. © International Science Press.