15 citations · 18 across the 3 of their papers we have counts for
3 papers
Securing State Estimation Under Sensor and Actuator Attacks: Theory and Design
Mehrdad Showkatbakhsh, Yasser Shoukry, Suhas Diggavi +1
This paper discusses the problem of estimating the state of a linear time-invariant system when some of its sensors and actuators are compromised by an adversarial agent. In the mo…
Differentially Private Consensus-Based Distributed Optimization
Mehrdad Showkatbakhsh, Can Karakus, Suhas Diggavi
Data privacy is an important concern in learning, when datasets contain sensitive information about individuals. This paper considers consensus-based distributed optimization under…
Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise
Mehrdad Showkatbakhsh, Can Karakus, Suhas Diggavi
Data privacy is an important concern in machine learning, and is fundamentally at odds with the task of training useful learning models, which typically require the acquisition of…