Reputation systems make the users of a distributed application accountable for their behavior. The reputation of a user is computed as an aggregate of the feedback provided by other users in the system. Truthful feedback is clearly a prerequisite for computing a reputation score that accurately represents the behavior of a user. However, it has been observed that users often hesitate in providing truthful feedback, mainly due to the fear of retaliation. Privacy preserving reputation systems enable users to provide feedback in a private and thus uninhibited manner. In this paper, we describe analysis frameworks for reputation systems and privacy preserving reputation systems. We use these analysis frameworks to review and compare the existing privacy preserving reputation systems in the literature. We identify the strengths and weaknesses of the various systems. We also discuss some open challenges.