Location-based services (LBS) have become an immensely valuable source of real-time information and guidance. Nonetheless, the potential abuse of users' sensitive personal data by an LBS server is evolving into a serious concern. Privacy concerns in LBS exist on two fronts: location privacy and query privacy. In this paper we investigate issues related to query privacy. In particular, we aim to prevent the LBS server from correlating the service attribute, e.g., bar/tavern, in the query to the user's real-world identity. Location obfuscation using spatial generalization aided by anonymization of LBS queries is a conventional means to this end. However, effectiveness of this technique would abate in continuous LBS scenarios, i.e., where users are moving and recurrently requesting for LBS. In this paper, we present a novel query-perturbation-based scheme that protects query privacy in continuous LBS even when user-identities are revealed. Unlike most exiting works, our scheme does not require the presence of a trusted third party.