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An overview of information-theoretic security and privacy: Metrics, limits and applications
This tutorial reviews fundamental contributions to information security. An integrative
viewpoint is taken that explains the security metrics, including secrecy, privacy, and others …
viewpoint is taken that explains the security metrics, including secrecy, privacy, and others …
Recent advances in deep learning theory
Deep learning is usually described as an experiment-driven field under continuous criticizes
of lacking theoretical foundations. This problem has been partially fixed by a large volume of …
of lacking theoretical foundations. This problem has been partially fixed by a large volume of …
Shredder: Learning noise distributions to protect inference privacy
F Mireshghallah, M Taram, P Ramrakhyani… - Proceedings of the …, 2020 - dl.acm.org
A wide variety of deep neural applications increasingly rely on the cloud to perform their
compute-heavy inference. This common practice requires sending private and privileged …
compute-heavy inference. This common practice requires sending private and privileged …
Tunable measures for information leakage and applications to privacy-utility tradeoffs
We introduce a tunable measure for information leakage called maximal-leakage. This
measure quantifies the maximal gain of an adversary in inferring any (potentially random) …
measure quantifies the maximal gain of an adversary in inferring any (potentially random) …
Estimation efficiency under privacy constraints
We investigate the problem of estimating a random variable Y under a privacy constraint
dictated by another correlated random variable X. When X and Y are discrete, we express …
dictated by another correlated random variable X. When X and Y are discrete, we express …
Locally private non-asymptotic testing of discrete distributions is faster using interactive mechanisms
We find separation rates for testing multinomial or more general discrete distributions under
the constraint of alpha-local differential privacy. We construct efficient randomized …
the constraint of alpha-local differential privacy. We construct efficient randomized …
Information-theoretic approaches to privacy in estimation and control
E Nekouei, T Tanaka, M Skoglund… - Annual Reviews in …, 2019 - Elsevier
Network control systems (NCSs) heavily rely on information and communication
technologies for sharing information between sensors and controllers as well as controllers …
technologies for sharing information between sensors and controllers as well as controllers …
Simple binary hypothesis testing under local differential privacy and communication constraints
We study simple binary hypothesis testing under local differential privacy (LDP) and
communication constraints. Our results are either minimax optimal or instance optimal: the …
communication constraints. Our results are either minimax optimal or instance optimal: the …
Fundamentals of physical layer anonymous communications: Sender detection and anonymous precoding
Z Wei, F Liu, C Masouros… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In the era of big data, anonymity is recognized as an important attribute in privacy-preserving
communications. The existing anonymous authentication and routing designs are applied at …
communications. The existing anonymous authentication and routing designs are applied at …
Quantifying privacy via information density
L Grosse, S Saeidian, P Sadeghi… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
We examine the relationship between privacy metrics that utilize information density to
measure information leakage between a private and a disclosed random variable. Firstly, we …
measure information leakage between a private and a disclosed random variable. Firstly, we …