Research Overview

This research aims to enhance the safety and security of the operation of multi-agent systems.

Introduction: Multi-agent systems (MASs) have recently gained significant attention for their ability to solve complex engineering problems. The main goal in operating MASs is to achieve consensus among agents (e.g., UAVs, robots, autonomous vehicles) to satisfy their collaborative objectives. For instance, the vehicle dynamics for urban air mobility (UAM) operation can be represented through MAS, where UAM aerial vehicles (AVs) can achieve their UAM missions (e.g., formation control and velocity-matching consensus) by exchanging their information (position and velocity) with neighbors. Therefore, the communication between agents plays a significant role in the operation of MASs. However, this communication-based structure results in MASs being vulnerable to various malicious entities, such as cyberattacks, disturbances, and system faults. Therefore, it is important to develop advanced control algorithms to enhance the safety and security of MASs despite those threats.

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The following is the summary of our ongoing research:

Reactive Multi-Agent Defense Strategy

Objective: In this research topic, we aim to design resilient control and estimation algorithms that can directly mitigate the impact of adversities. To this end, we developed resilient sensor fusion and estimation algorithms that can filter out the malicious data/information embedded in measurement output. The following videos show the realistic UAM operation in Greater Atlanta with four AVs conducting reference tracking control with formation flight. The left video shows the off-nominal UAM operation with a high risk of collisions. However, the right video shows the resilient UAM operation using our proposed method with high-assured safety.

Publication:
S. Hwang, M. Cho, and I. Hwang, "An Observer-Based Resilient Control Strategy for Leader-Follower Multi-Agent Systems Under False-Data-Injection Attacks", 2024 Midwest Workshop in Control and Game Theory, April 27-28, 2024, Northwestern University, Illinois, USA.

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Proactive Multi-Agent Defense Strategy

Objective: In this research topic, we focus on developing security metrics for multi-AVs that can measure the potential risk (e.g., collisions) by stealthy attacks. We specifically utilize an over-approximated ellipsoidal reachable set through the Lyapunov stability criterion. This reachable set (red-shaded ellipsoids) indicates the level of performance degradation (e.g., trajectory deviation) posed by attacks at certain future time steps. If there are overlaps between reachable sets, we can identify that associated AVs may have potential risks in terms of collisions during operation.

Publication:
S. Hwang, M. Cho, S. Kim, and I. Hwang, "An LMI-Based Risk Assessment of Leader-Follower Multi-Agent System Under Stealthy Cyberattacks." IEEE Control Systems Letters, vol. 7, pp. 419-2424, 2023 (also presented at the 62nd IEEE Conference on Decision and Control).
M, Cho, S. Hwang, and I. Hwang, "Risk Assessment of Multi-Agent System Under Denial-of-Service Cyberattacks Using Reachable Set Synthesis." 2024 American Control Conference (ACC), pp. 1293-1298. IEEE, Toronto, Canada, July. 2024.

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This research aims to enhance the operational safety of UAVs under adversarial environments.

Introduction: One of the key aspects of researching Unmanned Aerial Vehicles (UAVs) is how to enhance or fully guarantee their operational safety? UAVs are particularly vulnerable to various malicious threats, such as disturbances, wind gusts, and cyberattacks. For example, in terms of cybersecurity, GPS sensors on UAVs can be easily compromised by cyberattacks, leading to significant degradation in operational performance, such as tracking a destination. To address this challenge, we aim to develop safety-critical control and assurance algorithms to enhance the operational safety of UAVs.

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The following is the summary of our ongoing research:

Risk Assessment for UAVs under GPS Stealthy Attacks

Objective: In this research, we aim to develop a model-based risk assessment methodology for quadrotor UAVs under GPS stealthy attacks. These attacks represent particularly severe cyber threats due to their covert nature, allowing them to significantly degrade system performance without triggering alarms. To address this challenge, we propose a reachability-based security metric to quantify the extent of performance degradation caused by potential stealthy attacks. This methodology can be applicable to UAV tracking control operations in urban-like environments, where GPS sensor values are highly susceptible to compromise by attackers.

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Publication: To be appear

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