Abstract
Under the Internet of things paradigm, cyber-physical systems offer various applications in daily or industrial lives, whereas sensitive information about individuals may be collected to increase the system efficiency. When a piece of correlated public information is revealed, private information can be easily captured. Because of such risks, we are focusing on the privacy problem while analyzing privacy jointly with data utility regarding the utility privacy trade-off. We analyze this trade-off for communication systems, where noise is inevitable. This trade-off is first studied for binary models and then continuous sources are investigated. Finally, implementation perspective of the trade-off is detailed and tested with software-defined radios for an orthogonal frequency division multiplexing system model.
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