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Research

I am always open for collaboration to explore something new or related. General topics of interest are

  • physical layer privacy and security

  • information theory

  • statistical learning and inference

  • (wireless) communications

  • signal processing & algorithms

  • networked control

My publication list can be found here (pdf file). In my publications, I follow the principle that authors are ordered according to their contributions (first author contributed most, last author contributed least). Here are some selected more concrete research topics on which I have recently worked on (incomplete):

Privacy-preserving Learning

Due to privacy reasons, disclosure of data might not be possible so that value of the data is not exploited. It is therefore important to develop and analyze data analysis tools with disclosure control and provable privacy guarantees for learning and sharing of data. The goal is to develop clever mechanisms that maximize the utility while satisfying the suitable privacy constraints.

Biometric Identification Systems

Biometric data brings convenience in systems, but it also invokes privacy and secrecy issues. Physical layer security provides strong strong privacy and security guarantees. Thus, how to design optimal biometric identification systems and what are the optimal trade-offs?

  • "Incremental Design of Secure Biometric Identification and Authentication," ISIT 2021, jointly with L. Zhou and M. Skoglund.

  • "Privacy-Preserving Identification Systems with Noisy Enrollment," IEEE T-IFS, May 2021 jointly with L. Zhou, M. T. Vu, and M. Skoglund.

  • "Two-Stage Biometric Identification Systems without Privacy Leakage," IEEE J. on Selected Areas in Inform. Theory, March 2021 jointly with L. Zhou, M. T. Vu, and M. Skoglund.

Data-driven Calibration Algorithms

The basic working mechanism of a sensor is to convert a specific physical quantity to an electrical signal. The physical model of the sensor however might not incorporate all dependencies of environmental factors. One vital approach is adjust a calibration parameter to compensate for the remaining environmental factors. How to design efficient algorithms to learn the dependency and provide mechanisms that provide a belief function on the sensor measurements?

Fundamental Bounds in Distributed Decision-making

In 1968, Witsenhausen formulated a two-stage control problem for which he showed that non-linear policies outperform the best linear policy. Therewith, he disproved the conjecture that the optimality of linear strategies for centralized linear quadratic Gaussian control problems extends to decentralized systems. The optimal solution of this toy problem remains unsolved, but it is an interesting study object since it points on a very fundamental issue. We take a fresh approach approach deriving fundamental bounds using coordination coding results.

Smart Meter Privacy

Energy consumption profiles contain lots of private information about consumer habits and actions. Thus, privacy becomes more and more an issue with increasing resolution of smart meters in future smart grids. How can we assess the privacy risk and how can we protect the consumer privacy? Can we manipulate the energy consumption profile to enhance the privacy level? What are the fundamental limits to protect against un-authorised inference on consumers behaviour and habits?

A tutorial for WIFS 2018 jointly with D. Gunduz, Imperial College London, can be found here (pdf slides ).

Identification

Identification of a user or item is a key task of a search in a database, e.g. for authentication. However with high dimensional data, the storage size and search complexity become the critical parameters. If the identification additionally deals with personal data, then we also face a privacy problem. To deal with such problems, we study fundamental properties of a two stage identification system with pre-processing.

Parts of the work have been presented in an invited talk at DigiCosme in Oct 2017 (slides).

Secure Estimation

Estimation and tracking the state of a dynamical system is essential for future cyber-physical systems. However, we may want to keep the state keep secret. How can we achieve a secure communication over an uncertain channel so that an unauthorized receiver will not be able to track the state? What are the fundamental necessary and sufficient conditions?

  • "Secure Estimation and Zero-Error Secrecy Capacity," IEEE T-AC, Dec 2016, accepted Nov 2017, jointly with M. Wiese, K.-H. Johannsson, P. Papadimitratos, H. Sandberg, and M. Skolglund

  • "Secure Estimation for Unstable Systems," in Proc. IEEE Conference on Decision and Control, Las Vegas, Dec 2016, joinlty with M. Wiese, K.-H. Johannsson, P. Papadimitratos, H. Sandberg, and M. Skolglund.

  • "Secure Distributed Estimation of Linear Systems," in Proc. IEEE Conference on Communications and Network Security, Philadelphia, PA, Oct 2016, joinlty with M. Wiese.

Distributed Detection with Privacy

Consider a distributed detection problem where links are attacked by an eavesdropper. How to achieve a privacy-aware system design considering a detection-theoretic operational privacy metric? What kind of detection strategies are sufficient to consider for optimization? Some selected publications:

  • "Privacy-Aware Distributed Bayesian Detection," IEEE Journal of Selected Areas in Signal Processing, Oct. 2015 jointly with Z. Li.

  • "Tandem Distributed Bayesian Detection with Privacy Constraints," Proc. IEEE ICASSP, May 2014, jointly with Z. Li.

  • "Parallel Distributed Neyman-Pearson Detection with Privacy Constraints," Proc. IEEE ICC Workshop, June 2014, jointly with Z. Li and J. Jalden.

  • "Differential Privacy in Parallel Distributed Bayesian Detections," Proc. Fusion, July 2014, jointly with Z. Li.

Here you can find an overview presentation (pdf) I gave at Princeton in June 2014.

Optimal Transmit Strategies with Per-Antenna Power Constraints

The capacity of wireless channels can be significantly increased if we use multiple antennas at the transmitter and receiver. Since each transmit antenna has its own power amplifier, it is reasonable to assume that we have per-antenna power constraint. Thus, what are the optimal transmit strategies taking this into account? How can we compute the optimal transmit strategies?

Secure Source Coding Problems

Consider a distributed source coding setup where the communication is eavesdropped. What is the optimal coding strategy limiting the information leakage to an eavesdropper? What are bounds on the optimal trade-off between rates over public and private channels, distortion, and information leakage? Some selected publications:

  • "Secure Block Source Coding with Sequential Encoding," IEEE J. Sel. Areas in Inform. Theory, March 2021, jointly with H. Ghourchian, F. Stavrou, M. Skoglund.

  • "Polar code for secure Wyner-Ziv coding," IEEE WIFS 2016, joinlty with M. T. Vu and M. Skoglund.

  • "Secure Source Coding with Action-dependent Side Information," in IEEE Transactions in Information Theory, Dec. 2015, jointly with K. Kittichokechai, Y.-K. Chia, and M. Skoglund.

  • "Lossy Source Coding with Reconstruction Privacy," Proc. IEEE ISIT June 2014, jointly with K. Kittichokechai, and M. Skoglund.

  • "Secure Successive Refinement with Degraded Side Information," Proc. ISIT June 2014, jointly with D. Xu, K. Kittichokechai, and M. Skoglund.

  • "Secure Source Coding with a Public Helper," IEEE Trans. Inform. Theory, Nov 2016, jointly with K. Kittichokechai, Y.-K. Chia, M. Skoglund, and T. Weissman.

Broadcast Channel with RX Message Cognition

Consider communication problems over a broadcast channel where the receivers have (partial) knowledge about messages to be transmitted to other receivers. What is the optimal coding strategy? Considering (vector-valued) Gaussian channels, what is the optimal transmit strategy/input distribution? Some selected publications:

  • "Bidirectional Broadcast Channel with Random States Non-causally Known at the Encoder," IEEE Trans. Inform. Theory, Jan. 2013, jointly with M. Skoglund.

  • "Broadcast Capacity Regions with Three Receivers and Message Cognition," Proc. ISIT, July 2012, jointly with R. Timo, and M. Wigger.

  • "Optimal Transmit Strategy for the MIMO Bidirectional Broadcast Channel," IEEE Trans. Commun., Dec. 2009, jointly with E. Jorswieck, R. Wyrembelski, and H. Boche.

Multi-terminal Networked Control

Consider a multi-terminal Gaussian closed-loop control setup where the plant observations are communicated over Gaussian channels to the controller(s). What are necessary and sufficient conditions for mean-square stability? What are suitable/optimal communication and control strategies?

  • "Stabilization Over Gaussian Networks," IEEE Trans. Autom. Control, Sept. 2014, jointly with A. Zaidi, S. Yuksel, and M. Skoglund.

  • "On Optimal Policies for Control and Estimation Over a Gaussian Relay Channel," Automatica, Sept. 2013, jointly A. Zaidi, S. Yuksel, and M. Skoglund.

  • "Sufficient Conditions for Closed-Loop Control Over Multiple-Access and Broadcast Channels," Proc. CDC, Dec. 2010, jointly with A. Zaidi, and M. Skoglund.

Approximation of Gaussian Mixture Distribution

Consider a Gaussian mixture distribution with a very large number of components. How can I approximate the entropy of such distribution? Which terms are most relevant and how to merge and prune other terms?

Complexity efficient receiver algorithm for IEEE802.11p

Wireless communication in vehicular environment is challenging due to the variation of the channel state. How can we improve the receiver performance in such environments? How can we efficiently estimate the channel state and decode the payload in IEEE802.11p communication?

  • "Low Complexity Scalable Iterative Algorithms for IEEE 802.11p Receivers," IEEE Transactions on Vehicular Technology, Sept. 2015, jointly with O. Goubet, G. Baudic, and F. Gabry.

Note: List of selected research topics and results is subject to be revised\updated\completed… Here, you can find a word cloud created with from my publication titles 2010-2015.