activity
20162026
most citedDifferential Privacy for Eye Tracking with Temporal Correlations

65 citations · 197 across the 32 of their papers we have counts for

collaborators

44 papers

cs.IT2026

Digital-Twin-Referenced Belief-Guided Q-Learning for Jammer Identification and Beam-Power Control in a mmWave Model

Parmida Geranmayeh, Onur Günlü

Digital Twin (DT) combined with reinforcement learning (RL) can support adaptive resource allocation and security-aware decision-making by comparing expected and observed network b…

cs.IT2026

Secure OFDM-IM ISAC With Artificial-Noise-Aided Index Deception

Ufuk Altun, Onur Günlü

We propose an artificial noise (AN)-aided, secure OFDM with index modulation (OFDM-IM) framework for integrated sensing and communication (ISAC). Consider a security-critical scena…

cs.IT2026

Bayesian-Guided Cooperative RL Beamforming for Wireless Adversarial User Detection

Parmida Geranmayeh, Onur Günlü

In next-generation wireless networks, communication systems are expected to go beyond simple data transmission and simultaneously provide high data rates, efficiency, and security.…

cs.IT2026

EML-AirComp: Layered Over-the-Air Computation from a Single Nomographic Gate

Onur Günlü

Over-the-air computation (AirComp) exploits multiple-access superposition to compute functions of distributed data without separately decoding all terminal messages. We study a reu…

cs.IT2026

6G Sensing Security: Distributed Game-Theoretic RL for Urban Beamforming and Attacker Detection

Parmida Geranmayeh, Onur Günlü

In next-generation networks, communication systems will no longer be limited to data transmission and will be expected to acquire awareness of the surrounding environment. This lea…

cs.IT2026

ISAC Privacy: Challenges and Solutions for 6G

Onur Günlü, Stefano Tomasin, João P. Vilela +4

Integrated sensing and communication (ISAC) is a promising feature of future communication networks. While spatial sensing can improve network performance and enable external servi…

cs.IT2026

Secure Integrated Sensing and Communication: Information Theory Offers Insights

Truman Welling, Onur Günlü, Aylin Yener

Integrated sensing and communication (ISAC) combines sensing and communication within a shared system framework by using the same transmitted signal for both objectives. ISAC can i…

cs.IT2026

Secure Rate-Distortion-Perception: A Randomized Distributed Function Computation Approach for Realism

Gustaf Åhlgren, Onur Günlü

Fundamental rate-distortion-perception (RDP) trade-offs arise in applications requiring maintained perceptual quality of reconstructed data, such as neural image compression. When…

cs.IT2026★ 3 cited

Deep Randomized Distributed Function Computation (DeepRDFC): Neural Distributed Channel Simulation

Didrik Bergström, Onur Günlü

The randomized distributed function computation (RDFC) framework, which unifies many cutting-edge distributed computation and learning applications, is considered. An autoencoder (…

cs.IT2026

Randomized Distributed Function Computation (RDFC): Ultra-Efficient Semantic Communication Applications to Privacy

Onur Günlü

We establish the randomized distributed function computation (RDFC) framework, in which a sender transmits just enough information for a receiver to generate a randomized function…

cs.CR2025

Multi-Domain Security for 6G ISAC: Challenges and Opportunities in Transportation

Musa Furkan Keskin, Muralikrishnan Srinivasan, Onur Gunlu +5

Integrated sensing and communication (ISAC) will be central to 6G-enabled transportation, providing both seamless connectivity and high-precision sensing. However, this tight integ…

cs.IT2025

Feedback Lunch: Learned Feedback Codes for Secure Communications

Yingyao Zhou, Natasha Devroye, Onur Günlü

We consider reversely-degraded secure-communication channels, for which the secrecy capacity is zero if there is no channel feedback. Specifically, we focus on a seeded modular cod…

cs.IT2025

Forward-Forward Autoencoder Architectures for Energy-Efficient Wireless Communications

Daniel Seifert, Onur Günlü, Rafael F. Schaefer

The application of deep learning to the area of communications systems has been a growing field of interest in recent years. Forward-forward (FF) learning is an efficient alternati…

cs.IT2025

Multi-hop Deep Joint Source-Channel Coding with Deep Hash Distillation for Semantically Aligned Image Recovery

Didrik Bergström, Deniz Gündüz, Onur Günlü

We consider image transmission via deep joint source-channel coding (DeepJSCC) over multi-hop additive white Gaussian noise (AWGN) channels by training a DeepJSCC encoder-decoder p…

eess.SP2025★ 6 cited

The Role of ISAC in 6G Networks: Enabling Next-Generation Wireless Systems

Muhammad Umar Farooq Qaisar, Weijie Yuan, Onur Günlü +6

The commencement of the sixth-generation (6G) wireless networks represents a fundamental shift in the integration of communication and sensing technologies to support next-generati…

cs.CR2025

Exact Bias of Linear TRNG Correctors -- Spectral Approach

Maciej Skorski, Francisco-Javier Soto, Onur Günlü

Using Fourier analysis, this paper establishes near-optimal security bounds for linear correctors commonly used in True Random Number Generators (TRNGs), expressed through code wei…

cs.IT2025

Communication-Efficient Distributed Computing Through Combinatorial Multi-Access Models

Shanuja Sasi, Onur Günlü

This paper explores the multi-access distributed computing (MADC) model, a novel distributed computing framework where mapper and reducer nodes are distinct entities. Unlike tradit…

cs.LG2025

Secure Best Arm Identification in the Presence of a Copycat

Asaf Cohen, Onur Günlü

Consider the problem of best arm identification with a security constraint. Specifically, assume a setup of stochastic linear bandits with arms of dimension . In each arm pu…

cs.IT2025

Novel Constructions for Computation and Communication Trade-offs in Private Coded Distributed Computing

Shanuja Sasi, Onur Günlü

Distributed computing enables scalable machine learning by distributing tasks across multiple nodes, but ensuring privacy in such systems remains a challenge. This paper introduces…

cs.IT2024

Modular Neural Wiretap Codes for Fading Channels

Daniel Seifert, Onur Günlü, Rafael F. Schaefer

The wiretap channel is a well-studied problem in the physical layer security literature. Although it is proven that the decoding error probability and information leakage can be ma…

cs.IT2024

Secure Coded Distributed Computing

Shanuja Sasi, Onur Günlü

In this paper, we consider two critical aspects of security in the distributed computing (DC) model: secure data shuffling and secure coded computing. It is imperative that any ext…

cs.IT2024

Rate-limited Shuffling for Distributed Computing

Shanuja Sasi, Onur Günlü

This paper studies the shuffling phase in a distributed computing model with rate-limited links between nodes. Each node is connected to all other nodes via a noiseless broadcast l…

cs.IT2023★ 1 cited

Secure Integrated Sensing and Communication

Onur Günlü, Matthieu R. Bloch, Rafael F. Schaefer +1

This work considers the problem of mitigating information leakage between communication and sensing in systems jointly performing both operations. Specifically, a discrete memoryle…

cs.IT2022

Concatenated Classic and Neural (CCN) Codes: ConcatenatedAE

Onur Günlü, Rick Fritschek, Rafael F. Schaefer

Small neural networks (NNs) used for error correction were shown to improve on classic channel codes and to address channel model changes. We extend the code dimension of any such…