29 citations · 36 across the 28 of their papers we have counts for
22 papers · 1 filter
Contraction and Statistical Inference under Privacy for Uniformly Bounded Distributions
Leonhard Grosse, Sara Saeidian, Tobias J. Oechtering +1
We investigate -interior pointwise maximal leakage (PML) as a tool for contraction analyses and disclosure control. Based on the strong adversarial threat models from maximal le…
Generalizing the Fano inequality further
Raghav Bongole, Tobias J. Oechtering, Mikael Skoglund
Interactive statistical decision making (ISDM) features algorithm-dependent data generated through interaction. Existing information-theoretic lower bounds in ISDM largely target e…
Dobrushin Coefficients of Private Mechanisms Beyond Local Differential Privacy
Leonhard Grosse, Sara Saeidian, Tobias J. Oechtering +1
We investigate Dobrushin coefficients of discrete Markov kernels that have bounded pointwise maximal leakage (PML) with respect to all distributions with a minimum probability mass…
Risk level dependent Minimax Quantile lower bounds for Interactive Statistical Decision Making
Raghav Bongole, Amirreza Zamani, Tobias J. Oechtering +1
Minimax risk and regret focus on expectation, missing rare failures critical in safety-critical bandits and reinforcement learning. Minimax quantiles capture these tails. Three str…
Integrated Sensing and Communication with Distributed Rate-Limited Helpers
Yiqi Chen, Holger Boche, Tobias J. Oechtering +1
This paper studies integrated sensing and communication (ISAC) systems with two rate-limited helpers who observe the channel state sequence and the feedback sequence, respectively.…
An Information Geometric Approach to Local Information Privacy with Applications to Max-lift and Local Differential Privacy
Amirreza Zamani, Parastoo Sadeghi, Mikael Skoglund
We study an information-theoretic privacy mechanism design, where an agent observes useful data and wants to reveal the information to a user. Since the useful data is correlat…
Multi-terminal Strong Coordination over Noisy Channels with Encoder Co-operation
Viswanathan Ramachandran, Tobias J. Oechtering, Mikael Skoglund
We investigate the problem of strong coordination over a multiple-access channel (MAC) with cribbing encoders. In this configuration, two encoders observe independent and identical…
Bounds on the privacy amplification of arbitrary channels via the contraction of -divergence
Leonhard Grosse, Sara Saeidian, Tobias J. Oechtering +1
We examine the privacy amplification of channels that do not necessarily satisfy any LDP guarantee by analyzing their contraction behavior in terms of -divergence, an -dive…
Private Semantic Communications with Separate Blind Encoders
Amirreza Zamani, Mikael Skoglund
We study a semantic communication problem with a privacy constraint where an encoder consists of two separate parts, e.g., encoder 1 and encoder 2. The first encoder has access to…
Multi-terminal Strong Coordination subject to Secrecy Constraints
Viswanathan Ramachandran, Tobias J. Oechtering, Mikael Skoglund
A fundamental problem in decentralized networked systems is to coordinate actions of different agents so that they reach a state of agreement. In such applications, it is additiona…
Improving Achievability of Cache-Aided Private Variable-Length Coding with Zero Leakage
Amirreza Zamani, Mikael Skoglund
A statistical cache-aided compression problem with a privacy constraint is studied, where a server has access to a database of files, , each of size bits and…
On Information Theoretic Fairness: Compressed Representations With Perfect Demographic Parity
Amirreza Zamani, Borja Rodríguez-Gálvez, Mikael Skoglund
In this article, we study the fundamental limits in the design of fair and/or private representations achieving perfect demographic parity and/or perfect privacy through the lens o…
Information Density Bounds for Privacy
Sara Saeidian, Leonhard Grosse, Parastoo Sadeghi +2
This paper explores the implications of guaranteeing privacy by imposing a lower bound on the information density between the private and the public data. We introduce a novel and…
Multi-Task Private Semantic Communication
Amirreza Zamani, Sajad Daei, Tobias J. Oechtering +1
We study a multi-task private semantic communication problem, in which an encoder has access to an information source arbitrarily correlated with some latent private data. A user h…
Distribution-Preserving Integrated Sensing and Communication with Secure Reconstruction
Yiqi Chen, Tobias Oechtering, Holger Boche +2
Distribution-preserving integrated sensing and communication with secure reconstruction is investigated in this paper. In addition to the distortion constraint, we impose another c…
Quantifying Privacy via Information Density
Leonhard Grosse, Sara Saeidian, Parastoo Sadeghi +2
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 p…
Private Variable-Length Coding with Non-zero Leakage
Amirreza Zamani, Tobias J. Oechtering, Mikael Skoglund
A private compression design problem is studied, where an encoder observes useful data , wishes to compress it using variable length code and communicates it through an unsecure…
Private Variable-Length Coding with Zero Leakage
Amirreza Zamani, Tobias J. Oechtering, Deniz Gündüz +1
A private compression design problem is studied, where an encoder observes useful data , wishes to compress it using variable length code and communicates it through an unsecure…
On General Capacity-Distortion Formulas of Integrated Sensing and Communication
Yiqi Chen, Tobias Oechtering, Mikael Skoglund +1
The integrated sensing and communication (ISAC) problem with general state and channel distributions is investigated. General formulas of the capacity-distortion tradeoff for the I…
Private Variable-Length Coding with Sequential Encoder
Amirreza Zamani, Tobias J. Oechtering, Deniz Gündüz +1
A multi-user private data compression problem is studied. A server has access to a database of files, , each of size bits and is connected to an encoder. The…
New Privacy Mechanism Design With Direct Access to the Private Data
Amirreza Zamani, Tobias J. Oechtering, Mikael Skoglund
The design of a statistical signal processing privacy problem is studied where the private data is assumed to be observable. In this work, an agent observes useful data , which…
Pointwise Maximal Leakage
Sara Saeidian, Giulia Cervia, Tobias J. Oechtering +1
We introduce a privacy measure called pointwise maximal leakage, generalizing the pre-existing notion of maximal leakage, which quantifies the amount of information leaking about a…