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The privacy risks for individuals are becoming more concrete in communication systems, and existing privacy protection methods may not be suitable in communication systems. Among existing privacy definitions, the utility privacy trade-off is proper evaluation model of privacy in communication systems due to its relation with information theory and rate distortion theory. In this paper, at first we theoretically investigate the utility privacy trade-off on noisy channels and derive the updated expressions for trade-off functions. Then, these functions are both simulated and tested with software defined radios (SDRs) for orthogonal frequency division multiplexing (OFDM) based wireless communication system.

Expanding usage of mobile technologies and devices causes new challenges, especially in terms of security. In the near future, the number of battery powered devices will also significantly increase. Current security approaches are not sufficient for these issues and high-complexity cryptographic techniques are not suitable for such devices. To address these problems, physical layer (PHY) security solutions have recently emerged. Some 5G candidate techniques such as full-duplex communication (FD) and artificial noise transmission (AN) are exploited in various PHY security solutions due to their performance advantages. In this study, a scenario resembling a factory environment is considered and security level is analyzed in real-time by utilizing FD and AN methods. The aim of this analysis is to investigate physically secure transmission regions and to expand these regions by intelligently using AN. Our proposed approach is evaluated in real-time with a testbed that consists of software defined radios (SDRs). Two devices with very different front-end characteristics are utilized as eavesdroppers to analyze hardware effects on the eavesdropping performance. As observed with experiments, robust secure regions can be created by the use of AN on eavesdroppers effectively.