Profile matching is a fundamental and significant step for mobile social services to build social relationships and share interests. Given the privacy and efficiency concerns of mobile platforms, we propose a cost-effective profile matching technique called S-Match for mobile social services in which matching operations are achieved in a privacy-preserving manner utilizing property-preserving encryption (PPE). Specifically, in this poster, we first analyze the challenges of directly using PPE for profile matching. Second, we introduce a solution based on entropy increase. Our initial results, with three real-world datasets, show that S-Match achieves at least an order of magnitude improvement over other relevant schemes.