Mobile computing based on wearable devices is considered as the important technology for supporting ubiquitous perceptual applications. It uses widespread sensors to continuously sense the environment information. Moreover, it also adopts short-range communication and data mining/machine learning to transmit and process the sensed data, respectively. Current work mainly focuses on designing and implementing new mobile applications, information gathering, product modality and friendly user interfaces. However, research on data security and privacy technology for wearable devices is still in its fancy. In the perspective of data analysts, researchers analyze the characteristics of diverse data in wearable devices and privacy threats targeting wearable devices. Moreover, they are particularly interested in human activity recognition techniques and data mining mechanisms based on multi-source sensing data. On the other hand, it is vital for privacy protectors of wearable devices to study on privacy preservation techniques in the following three aspects: cloud-assisted privacy preserving mechanisms, privacy-aware personal data publishing and policy-based access control. A case study regarding security and privacy for Fitbit, a kind of wearable devices for health tracking, is presented. At last, the technological approaches to preserve data security and privacy for wearable devices are summarized, and some open issues to be further studied are also raised.