Vulnerability of Building Energy Management Systems to Targeted False Data Injection Attacks: Comparative Analysis of Model Predictive Control and Proportional Integral Control

Centrala begrepp

Targeted false data injection attacks can significantly impact the performance and lifespan of building energy management systems, with model predictive control being more vulnerable than proportional integral control.

Sammanfattning

The paper investigates the vulnerability of building energy management systems (BMS) against targeted false data injection (FDI) attacks using proportional-integral (PI) and model predictive control (MPC) methods. The study focuses on a commercial building model with five rooms and examines the effectiveness of these control strategies in maintaining system performance and lifespan under FDI attacks.
The key findings are:

MPC controllers outperform PI controllers in terms of adaptability and efficiency under normal operating conditions. However, MPC controllers are more vulnerable to reducing heat pump lifespan during cyberattacks.

PI controllers rapidly counteract such attacks, protecting the heat pumps but at the expense of reduced valve lifetimes.

The targeted FDI attack on the south room temperature sensor was the most devastating, causing a 12% reduction in the lifetime of the heat pump under an MPC controller and a near thirty-fold overuse of flow valves under a PI controller.

The comparative analysis highlights the critical need for a robust control system in the face of evolving cybersecurity threats, which will be the focus of future research.

Statistik

Even a short-term FDIA can cause a 12% reduction in the lifetime of a heat-pump under an MPC controller.
A targeted FDIA can cause a near thirty-fold overuse of flow valves under a PI controller.

Citat

"The findings show that MPC controllers outperform PI controllers in adaptability and efficiency, yet they are more vulnerable to reducing heat pump lifespan during cyberattacks."
"Conversely, PI controllers rapidly counteract such attacks, protecting the heat pumps but at the expense of reduced valve lifetimes."

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Vulnerability of Building Energy Management against Targeted False Data Injection Attacks:Model Predictive Control vs. Proportional Integral

by Xiaoyu Ge,Ka... på arxiv.org 05-03-2024

https://arxiv.org/pdf/2312.03588.pdf

Djupare frågor

How can building energy management systems be designed to be more resilient against targeted false data injection attacks while maintaining high energy efficiency?

Building energy management systems can be designed to enhance resilience against targeted false data injection attacks while still maintaining high energy efficiency through several key strategies:

Implementing Secure Communication Protocols: Utilizing secure communication protocols such as encryption and authentication can help prevent unauthorized access and manipulation of data, reducing the risk of false data injection attacks.

Intrusion Detection Systems: Incorporating intrusion detection systems can help detect anomalies in data patterns, signaling potential false data injection attacks. By promptly identifying and mitigating these attacks, the system can maintain its integrity and efficiency.

Redundancy and Backup Systems: Building redundancy and backup systems can ensure that even if one part of the system is compromised by a cyber-attack, the overall functionality and energy efficiency of the system are not severely impacted.

Regular Security Audits and Updates: Conducting regular security audits and updates to identify and patch vulnerabilities in the system can significantly enhance its resilience against cyber threats, including false data injection attacks.

Utilizing Advanced Control Techniques: Leveraging advanced control techniques like Model Predictive Control (MPC) can improve the system's ability to adapt to changing conditions and mitigate the impact of false data injection attacks on energy efficiency.

By integrating these strategies into the design of building energy management systems, it is possible to create a more resilient infrastructure that can withstand targeted cyber-attacks while still maintaining high energy efficiency levels.

What are the potential trade-offs between cybersecurity and energy efficiency in the design of building energy management systems?

In the design of building energy management systems, there are several potential trade-offs between cybersecurity and energy efficiency that need to be carefully considered:

Resource Allocation: Investing in robust cybersecurity measures may require allocating resources that could otherwise be used to enhance energy efficiency. Balancing these priorities is crucial to ensure both aspects are adequately addressed.

Complexity vs. Security: Increasing the complexity of the system to improve energy efficiency may inadvertently introduce vulnerabilities that could be exploited by cyber-attacks. Simplifying the system for security purposes could impact its energy efficiency.

Response Time: Implementing stringent security measures may introduce delays in system response times, potentially affecting energy efficiency. Finding the right balance between security and operational efficiency is essential.

Data Privacy vs. Data Accessibility: Enhancing cybersecurity measures to protect sensitive data may restrict access to certain information that could be valuable for optimizing energy efficiency. Striking a balance between data privacy and accessibility is key.

Maintenance and Updates: Regular maintenance and updates are essential for both cybersecurity and energy efficiency. However, prioritizing one over the other could lead to vulnerabilities in the neglected aspect.

By understanding these trade-offs and carefully weighing the priorities of cybersecurity and energy efficiency in the design process, it is possible to create a system that effectively balances both aspects for optimal performance.

How can the insights from this study be applied to other cyber-physical systems beyond building energy management to enhance their resilience against targeted attacks?

The insights from this study can be applied to enhance the resilience of other cyber-physical systems against targeted attacks in the following ways:

Advanced Control Techniques: Implementing advanced control techniques like Model Predictive Control (MPC) can improve the adaptability and robustness of cyber-physical systems to mitigate the impact of targeted attacks.

Intrusion Detection Systems: Integrating intrusion detection systems into various cyber-physical systems can help detect and respond to anomalies or attacks promptly, safeguarding the system's integrity.

Secure Communication Protocols: Utilizing secure communication protocols in different cyber-physical systems can prevent unauthorized access and manipulation of data, reducing the risk of targeted attacks.

Regular Security Audits: Conducting regular security audits and updates across diverse cyber-physical systems can help identify vulnerabilities and strengthen defenses against potential attacks.

Redundancy and Backup Systems: Building redundancy and backup systems in other cyber-physical systems can ensure continuity of operations even in the face of targeted attacks, enhancing overall resilience.

By applying these insights and strategies to a broader range of cyber-physical systems, organizations can bolster their defenses and enhance the resilience of critical infrastructure against targeted cyber-attacks.