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This paper considers asymptotic perfect secrecy and asymptotic perfect estimation in distributed estimation for large sensor networks under threat of an eavesdropper, which has access to all sensor outputs. To measure secrecy, we compare the estimation performance at the fusion center and at eavesdropper in terms of their respective Fisher Information. We analyze the Fisher Information ratio between the fusion center and eavesdropper and derive the maximum achievable ratio when the channels between sensors and eavesdropper are noisy binary symmetric channels.

Different transforms are compared to extract bit sequences used in secret-key binding for highly-correlated physical-identifier outputs. A set of transforms that perform well in terms of decorrelation efficiency is applied to ring oscillator (RO) outputs to improve the reliability and uniqueness of the extracted sequence, information leakage to an eavesdropper about the secret key and RO outputs, secret-key length, and hardware cost.

We propose a simple protocol which allows two legitimate parties to exchange some confidential message over a wireless
channel with some chosen level of semantic security against passive eavesdroppers, and without needing either secret or public keys. The proposed method leverages the noisy and fading nature of the channel and exploits coding and all-or-nothing transforms to achieve the desired level of semantic security. We also define suitable metrics to estimate the semantic security level in the considered setting.

This is an overview poster on designing a privacy-preserving randomized requantization scheme which simultaneously guarantees local differential privacy and reduces bit-rate of input signals.

For more information, please check out the publication at IEEE Xplore:

S. Xiong, A.D. Sarwate, and N.B. Mandayam, “Randomized requantization with local differential privacy,” in Proceedings of the 41st International Conference on Acoustics, Speech and Signal Processing, March 2016.

This is an overview poster on designing a privacy-preserving randomized requantization scheme which simultaneously guarantees local differential privacy and reduces bit-rate of input signals.

For more information, please check out the publication at IEEE Xplore:

S. Xiong, A.D. Sarwate, and N.B. Mandayam, “Randomized requantization with local differential privacy,” in Proceedings of the 41st International Conference on Acoustics, Speech and Signal Processing, March 2016.

This is an overview poster on designing a privacy-preserving randomized requantization scheme which simultaneously guarantees local differential privacy and reduces bit-rate of input signals.

For more information, please check out the publication at IEEE Xplore:

S. Xiong, A.D. Sarwate, and N.B. Mandayam, “Randomized requantization with local differential privacy,” in Proceedings of the 41st International Conference on Acoustics, Speech and Signal Processing, March 2016.