Concealing Sequential and Spatiotemporal Patterns using Polynomial Sanitization

Earlier, Process of relevant pattern observation which is present in the database observed as a hurdle for database protection. Over the time, various approaches for hiding knowledge have emerged, mainly in the focus of Association rules and frequent item sets mining. This paper, have seen the problem in different view i.e., Knowledge hiding to the context where the data and extracted knowledge have a sequential structure. The concept of NP hardness is observed over the sequential pattern hiding. A polynomial sanitization algorithm was adopted and implemented over the spatiotemporal patterns extracted from moving objects databases. Disseminating datasets of this kind presents a considerable opportunity for knowledge patterns of interest. The developed model is kept under the attack, which exploits the knowledge of underlying road networks.