A health social network is an online information service which facilitates information sharing between closely related members of a community with the same or a similar health condition. Over the years, many automated recommender systems have been developed for social networking in order to help users find their communities of interest. For health social networking, the ideal source of information for measuring similarities of patients is the medical information of the patients. However, it is not desirable that such sensitive and private information be shared over the Internet. This is also true for many other security sensitive domains. A new information-sharing scheme is developed where each patient is represented as a small number of (possibly disjoint) d-words (discriminant words) and the d-words are used to measure similarities between patients without revealing sensitive personal information. The d-words are simple words like "food,'' and thus do not contain identifiable personal information. This makes our method an effective one-way hashing of patient assessments for a similarity measure. The d-words can be easily shared on the Internet to find peers who might have similar health conditions.