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The significant development in field of data collection and data storage technologies have provided transactional data to grow in data warehouses that reside in companies and public sector organizations. As the data is growing day by day, there has to be certain mechanism that could analyze such large volume of data. Data mining is a way of extracting the hidden predictive information from those data warehouses without revealing their sensitive information. Privacy preserving data mining (PPDM) is the recent research area that deals with the problem of hiding the sensitive information while analyzing data. Association Rule Hiding is one of the techniques of PPDM to hide association rules generated by Association Rule Generation Algorithms. In this paper we will provide a comparative theoretical analysis of Algorithms that have been developed for Association Rule Hiding.