3,642 research outputs found
Consensus of Multi-Agent Networks in the Presence of Adversaries Using Only Local Information
This paper addresses the problem of resilient consensus in the presence of
misbehaving nodes. Although it is typical to assume knowledge of at least some
nonlocal information when studying secure and fault-tolerant consensus
algorithms, this assumption is not suitable for large-scale dynamic networks.
To remedy this, we emphasize the use of local strategies to deal with
resilience to security breaches. We study a consensus protocol that uses only
local information and we consider worst-case security breaches, where the
compromised nodes have full knowledge of the network and the intentions of the
other nodes. We provide necessary and sufficient conditions for the normal
nodes to reach consensus despite the influence of the malicious nodes under
different threat assumptions. These conditions are stated in terms of a novel
graph-theoretic property referred to as network robustness.Comment: This report contains the proofs of the results presented at HiCoNS
201
Finite-Time Resilient Formation Control with Bounded Inputs
In this paper we consider the problem of a multi-agent system achieving a
formation in the presence of misbehaving or adversarial agents. We introduce a
novel continuous time resilient controller to guarantee that normally behaving
agents can converge to a formation with respect to a set of leaders. The
controller employs a norm-based filtering mechanism, and unlike most prior
algorithms, also incorporates input bounds. In addition, the controller is
shown to guarantee convergence in finite time. A sufficient condition for the
controller to guarantee convergence is shown to be a graph theoretical
structure which we denote as Resilient Directed Acyclic Graph (RDAG). Further,
we employ our filtering mechanism on a discrete time system which is shown to
have exponential convergence. Our results are demonstrated through simulations
How Physicality Enables Trust: A New Era of Trust-Centered Cyberphysical Systems
Multi-agent cyberphysical systems enable new capabilities in efficiency,
resilience, and security. The unique characteristics of these systems prompt a
reevaluation of their security concepts, including their vulnerabilities, and
mechanisms to mitigate these vulnerabilities. This survey paper examines how
advancement in wireless networking, coupled with the sensing and computing in
cyberphysical systems, can foster novel security capabilities. This study
delves into three main themes related to securing multi-agent cyberphysical
systems. First, we discuss the threats that are particularly relevant to
multi-agent cyberphysical systems given the potential lack of trust between
agents. Second, we present prospects for sensing, contextual awareness, and
authentication, enabling the inference and measurement of ``inter-agent trust"
for these systems. Third, we elaborate on the application of quantifiable trust
notions to enable ``resilient coordination," where ``resilient" signifies
sustained functionality amid attacks on multiagent cyberphysical systems. We
refer to the capability of cyberphysical systems to self-organize, and
coordinate to achieve a task as autonomy. This survey unveils the cyberphysical
character of future interconnected systems as a pivotal catalyst for realizing
robust, trust-centered autonomy in tomorrow's world
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