Farhad Farokhi

Farhad Farokhi is a Senior Lecturer (=Assistant/Associate Professor) at the Department of Electrical and Electronic Engineering at the University of Melbourne. Prior to that, he was a Research Scientist at the Information Security and Privacy Group at CSIRO’s Data61, a Research Fellow at the Department of Electrical and Electronic Engineering at the University of Melbourne, and Postdoctoral Fellow at KTH Royal Institute of Technology. In 2014, he received his PhD degree in Automatic Control from KTH Royal Institute of Technology. During his PhD studies, he was a visiting researcher at the University of California at Berkeley and the University of Illinois at Urbana-Champaign. Farhad has been the recipient of the IEEE Signal Processing Society Best Paper Award, Victorian State Government VESKI Victoria Fellowship as well as the McKenzie Fellow and the 2015 Early Career Researcher Award, 2020 MSE Excellence Award for Early Career Research, 2021 School of EMI Special Recognition Award from the University of Melbourne. He has been part of numerous projects on data privacy and cyber-security funded by the Defence Science and Technology Group, the Department of the Prime Minister and Cabinet, the Department of Environment and Energy, and CSIRO in Australia. His research interests include security and privacy in cyber-physical systems, such as smart grids and intelligent transportation systems.

E-mail: farhad<dot>farokhi<at>unimelb<dot>edu<dot>au

Available position: I am currently looking for PhD students with background in information theory, control theory, statistics, and optimization. They should be ideally interested in using information theory and control theory to answer questions on privacy, security, and fairness in optimization, machine learning, and cyber-physical systems! If you are interested, please send me an e-mail. A few project descriptions can be found here, here, here, and here.

Design of Real-time Optimisation Methods with Guaranteed Performance: Discovery Project, Australian Research Council (ARC)

The project aim is the development of a framework for the advancement of optimisation algorithms operating in real-time applications. This project expects to generate new knowledge in the area of systems theory and optimisation, and its application to time-varying problems. Expected outcomes of this project should lead to a new theoretical and practical framework that…

by Farhad Farokhi November 15, 2020

On the Privacy of TraceTogether, the Singaporean COVID-19 Contact Tracing Mobile App and Recommendations for Australia

Authors* (in Alphabetic Order): Hassan Asghar (Macquarie University), Farhad Farokhi (The University of Melbourne), Dali Kaafar (Macquarie University), Ben Rubinstein (The University of Melbourne). * The authors thank Vanessa Teague, cryptographer, from Thinking Cybersecurity for fruitful discussions. Introduction The Australian government is exploring the use of contact tracing mobile apps as a tool for public health officials…

by Farhad Farokhi March 30, 2020March 30, 2020

Non-stochastic privacy

A common thread or assumption among all provable privacy frameworks, such as information-theoretic privacy and differential privacy, is randomization for safeguarding privacy. The definition of differential privacy assumes the use of randomized functions and information theoretic tools used so far have been based on randomized random variables. However, many popular heuristic-based privacy-preserving methods, such as…

by Farhad Farokhi February 24, 2020February 24, 2020

Privacy of Dynamical Systems

Differential privacy is a natural candidate to alleviate privacy concerns in general. However, differential privacy literature most often deals with providing privacy-preserving responses to queries based on large, yet static datasets that are kept securely by a data curator while, in real-time analytics, the underlying data in possession of the curator changes over time. The…