Fast-paced data-to-decision systems are heavily dependent on the reliable sharing of sensor-derived information. At the same time a diverse collection of sensory information providers would want to exercise control over the information shared based on their perception of the risk of possible misuse due to sharing and also depending on the consumer requirements. To attain this utility vs. risk trade-off, information is subjected to varying but deliberate quality modifying transformations which we term as obfuscation. In this paper, treating privacy as the primary motivation for information control, we highlight initial considerations of using feature sharing as an obfuscation mechanism to control the inferences possible from shared sensory data. We provide results from an activity tracking scenario to illustrate the use of feature selection in identifying the various trade-off points. © 2012 ISIF (Intl Society of Information Fusi).