Passivity-based Attack Identification and Mitigation in Multi-Agent Systems

Conceptos Básicos

Secure consensus in multi-agent systems under FDI attacks using passivity-based approach and event-triggered observer feedback.

Resumen

• Addressing output consensus in passive multi-agent systems under FDI attacks.
• Proposing a passivity-based approach for attack detection and a switching controller for mitigation.
• Simulation examples support theoretical findings.
• Event-triggered observer feedback ensures system stability.
• Passivity inequality used for attack detection.
• System achieves practical output consensus under proposed control scheme.
• Different case studies with varying agent dynamics demonstrate the effectiveness of the proposed method.

Estadísticas

"The agents are usually under-actuated where p < m."
"Attack signal ua is bounded and has a bounded derivative."
"The attack remains active for t ∈[2, 5]s."

Citas

"We propose a passivity-based approach for detecting FDI attacks on the system."
"Simulation examples are provided to support the theoretical findings."
"The system achieves practical output consensus under the controller’s action in the defense mode."

Ideas clave extraídas de

Passivity-based Attack Identification and Mitigation with Event-triggered Observer Feedback and Switching Controller

by Pushkal Puro... a las arxiv.org 03-26-2024

https://arxiv.org/pdf/2403.15697.pdf

Consultas más profundas

How can undetectable attacks impact the overall security of multi-agent systems?

Undetectable attacks pose a significant threat to the security of multi-agent systems as they can bypass traditional detection mechanisms and remain hidden within the system. These attacks can manipulate the behavior of agents, compromise data integrity, disrupt communication networks, and even cause system failures without being detected. Since undetectable attacks do not trigger any alarms or warnings, they have the potential to cause severe damage over time by subtly undermining the system's operations and objectives. This stealthy nature makes them particularly dangerous as they can persist unnoticed for extended periods, leading to long-term vulnerabilities and compromises in system security.

What are the potential limitations of relying on passivity-based approaches for attack detection?

While passivity-based approaches offer a robust framework for attack detection in multi-agent systems, there are certain limitations that need to be considered:

Dependency on System Dynamics: Passivity-based methods rely heavily on understanding and modeling the dynamics of the system accurately. Any inaccuracies or uncertainties in these models could lead to false positives or negatives in attack detection.
Vulnerability to Sophisticated Attacks: Advanced attackers may exploit loopholes or weaknesses in passivity-based algorithms to launch sophisticated attacks that evade detection mechanisms based on energy analysis.
Resource Intensive: Implementing passivity-based techniques often requires significant computational resources and real-time processing capabilities, which may pose challenges for resource-constrained systems.
Limited Scope: Passivity-based approaches may not be effective against all types of cyber-attacks or novel attack vectors that deviate from traditional patterns analyzed through energy considerations.

How can this research be extended to address attacks on the global communication network?

To extend this research towards addressing attacks on global communication networks within multi-agent systems, several key steps can be taken:

Incorporating Network Security Protocols: Integrate protocols such as encryption, authentication mechanisms (e.g., digital signatures), secure channels (e.g., VPNs), intrusion detection/prevention systems into network communications.
Implementing Anomaly Detection Algorithms: Develop anomaly detection algorithms that monitor network traffic patterns for deviations indicative of malicious activities like DDoS attacks, packet sniffing attempts, etc.
Utilizing Blockchain Technology: Explore blockchain technology for securing communication channels by establishing decentralized trust among agents while ensuring data integrity and confidentiality across distributed networks.
Enhancing Resilience Mechanisms: Implement redundancy measures like backup routes/links, failover configurations, load balancing strategies to mitigate disruptions caused by network-level cyber-attacks like denial-of-service (DoS) assaults.

By integrating these strategies with existing passivity-based frameworks for detecting local agent-level threats, researchers can create a comprehensive defense mechanism against both internal agent manipulations and external network-level intrusions within complex multi-agent environments with interconnected communication infrastructures