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Much of security research focuses on preventing an adversary from deciphering a message's content, but there are a number of applications that motivate the more challenging goal of ``covert'' communications: transmitter Alice conveying information to legitimate receiver Bob while preventing a capable and attentive adversary Willie from detecting the presence of the message.


We introduce the notion of Quality of Indicator (QoI) to assess the level of contribution by participants in threat intelligence sharing. We exemplify QoI by metrics of the correctness, relevance, utility, and uniqueness of indicators. We build a system that extrapolates the metrics using a machine learning process over a reference set of indicators.


Motivated by privacy issues in the Internet of Things systems, we generalize a proposed privacy-preserving packet obfuscation scheme to guarantee differential privacy. We propose a locally differentially private packet obfuscation mechanism as a defense against packet-size side-channel attacks in IoT networks. We formulate the problem as an optimization over a conditional probability distribution (channel) between the original and obfuscated packet sizes and show that the optimal set of obfuscated packet sizes is a strict subset of the set of original packet sizes.


The field of quantum computing is based on the laws of quantum mechanics, including states superposition and entanglement. Quantum cryptography is amongst the most surprising applications of quantum mechanics in quantum information processing. Remote state preparation allows a known state to a sender to be remotely prepared at a receiver’s location when they prior share entanglement and transmit one classical bit.


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.