The problem of Byzantine resilience in distributed machine learning, aka Byzantine machine
learning, consists of designing distributed algorithms that can train an accurate model …

We investigate the vulnerabilities of consensus-based distributed optimization protocols to
nodes that deviate from the prescribed update rule (eg, due to failures or adversarial …

Resilient and robust distributed control protocols for multiagent systems under attacks on
sensors and actuators are designed. A distributed H∞ control protocol is designed to …

This paper addresses the problem of distributed multi-agent optimization in which each
agent i has a local cost function hi (x), and the goal is to optimize a global cost function that …

Though recent advancements in dc microgrids are largely based on distributed control
strategies to enhance reliability, their susceptibility to cyber attacks still remains a …

As the cyber-attack is becoming one of the most challenging threats faced by cyber-physical
systems, investigating the effect of cyber-attacks on distributed optimization and designing …

The growth in the number of devices connected to the Internet of Things (IoT) poses major
challenges in security. The integrity and trustworthiness of data and data analytics are …

This work analyzes the adverse effects of cyberphysical attacks on discrete-time distributed
multi-agent systems, and proposes a mitigation approach for attacks on sensors and …

Applications in environmental monitoring, surveillance and patrolling typically require a
network of mobile agents to collectively gain information regarding the state of a static or …

We study the problem of distributed state estimation of a linear time-invariant system by a
network of nodes, some of which are subject to adversarial attacks. We develop a secure …