In this paper, we introduce a new privacy protection property called p-sensitive k-anonymity. The existing kanonymity property protects against identity disclosure, but it fails to protect against attribute disclosure. The new introduced privacy model avoids this shortcoming. Two necessary conditions to achieve p-sensitive kanonymity property are presented, and used in developing algorithms to create masked microdata with p-sensitive k-anonymity property using generalization and suppression.