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Review of results on smart‐meter privacy by data manipulation, demand sha**, and load scheduling
Simple analysis of energy consumption patterns recorded by smart meters can be used to
deduce household occupancy. With access to higher‐resolution smart‐meter readings, we …
deduce household occupancy. With access to higher‐resolution smart‐meter readings, we …
On the privacy-utility trade-off with and without direct access to the private data
We study an information theoretic privacy mechanism design problem for two scenarios
where the private data is either observable or hidden. In the hidden private data scenario, an …
where the private data is either observable or hidden. In the hidden private data scenario, an …
Deep learning for privacy preservation in autonomous moving platforms enhanced 5G heterogeneous networks
Abstract 5G heterogeneous networks have become a promising platform to connect a
growing number of Internet-of-Things (IoT) devices and accommodate a wide variety of …
growing number of Internet-of-Things (IoT) devices and accommodate a wide variety of …
An operational approach to information leakage via generalized gain functions
We introduce a gain function viewpoint of information leakage by proposing maximal-
leakage, a rich class of operationally meaningful leakage measures that subsumes recently …
leakage, a rich class of operationally meaningful leakage measures that subsumes recently …
Data disclosure with non-zero leakage and non-invertible leakage matrix
We study a statistical signal processing privacy problem, where an agent observes useful
data and wants to reveal the information to a user. Since the useful data is correlated with …
data and wants to reveal the information to a user. Since the useful data is correlated with …
Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning
Differentially private mechanisms restrict the membership inference capabilities of powerful
(optimal) adversaries against machine learning models. Such adversaries are rarely …
(optimal) adversaries against machine learning models. Such adversaries are rarely …
Real-time privacy-preserving data release for smart meters
Smart Meters (SMs) are able to share the power consumption of users with utility providers
almost in real-time. These fine-grained signals carry sensitive information about users …
almost in real-time. These fine-grained signals carry sensitive information about users …
Non-cooperative games for privacy-preserving and cost-efficient smart grid energy management
In this paper, we design privacy-preserving and cost-efficient energy management strategies
for smart grid users that are equipped with renewable energy sources. The adversary is …
for smart grid users that are equipped with renewable energy sources. The adversary is …
A Design Framework for Strongly χ²-Private Data Disclosure
In this paper, we study a stochastic disclosure control problem using information-theoretic
methods. The useful data to be disclosed depend on private data that should be protected …
methods. The useful data to be disclosed depend on private data that should be protected …
Quantifying membership privacy via information leakage
Machine learning models are known to memorize the unique properties of individual data
points in a training set. This memorization capability can be exploited by several types of …
points in a training set. This memorization capability can be exploited by several types of …