Encrypted Control System with Automatic Disclosure of Residue Signal for Efficient Anomaly Detection

Основные понятия

The proposed dynamic encryption scheme automatically discloses the residue signal, enabling efficient anomaly detection in encrypted control systems without the secret key.

Аннотация

The paper proposes a dynamic encryption scheme that automatically discloses the residue signal, allowing for efficient anomaly detection in encrypted control systems without the secret key.

Key highlights:

• The scheme exploits the zero-dynamics of the system to generate encryptions of the initial state and input such that the effect of encryption on the residue signal remains identically zero.
• This disclosure of the residue signal enables a computing device without the secret key to directly and efficiently detect anomalies by comparing the residue signal with a threshold.
• The proposed encryption scheme is shown to be secure, as it only discloses the residue signal and no other information.
• The paper also demonstrates a method of utilizing the disclosed residue signal to operate an observer-based controller over encrypted data for an infinite time horizon without re-encryption.

Статистика

The system is described by the following equations:
x(t + 1) = F·x(t) + G·Enc(y(t)) mod q, x(0)=Enc(x0)
r(t) = H·x(t) + J·Enc(y(t)) mod q

Цитаты

"Anomaly detection is a protocol that detects integrity attacks on control systems by comparing the residue signal with a threshold."
"Implementing anomaly detection on encrypted control systems has been a challenge because it is hard to detect an anomaly from the encrypted residue signal without the secret key."

Ключевые выводы из

Learning with errors based dynamic encryption that discloses residue signal for anomaly detection

by Yeongjun Jan... в arxiv.org 04-04-2024

https://arxiv.org/pdf/2404.02574.pdf

Дополнительные вопросы

How can the proposed encryption scheme be extended to handle nonlinear systems?

The proposed encryption scheme, which leverages the zero-dynamics of the system to disclose the residue signal, can be extended to handle nonlinear systems by incorporating techniques from nonlinear control theory. One approach could involve approximating the nonlinear system with a linearized version around an operating point and then applying the encryption scheme to the linearized dynamics. This linearization process would involve computing the Jacobian matrices at the operating point to obtain the linearized state-space representation. The encryption scheme could then be applied to the linearized system in a similar manner as described for linear systems in the paper. Additionally, techniques such as feedback linearization or state-dependent scaling could be employed to handle the nonlinearity in the system while ensuring the disclosed residue signal remains accurate.

What are the potential limitations or drawbacks of disclosing the residue signal in terms of system security and privacy?

Disclosing the residue signal in an encrypted control system can have potential limitations and drawbacks in terms of system security and privacy. One major concern is that the disclosed residue signal could potentially leak sensitive information about the system dynamics, control strategies, or operational conditions. This information could be exploited by malicious actors to launch attacks on the system, compromise its integrity, or gain unauthorized access. Additionally, the disclosed residue signal may introduce vulnerabilities that could be exploited to infer additional information about the encrypted data or the system itself. Furthermore, if the encryption scheme is not robust enough, disclosing the residue signal could lead to potential security breaches or privacy violations, compromising the overall security of the system.

How could the ideas in this paper be applied to enhance the security of other types of cyber-physical systems beyond control systems?

The ideas presented in this paper, particularly the dynamic encryption scheme that discloses the residue signal for anomaly detection, can be applied to enhance the security of other types of cyber-physical systems beyond control systems. For example:

Smart Grids: The encryption scheme could be adapted to secure communication and data exchange in smart grid systems, ensuring the integrity and confidentiality of grid operations and data.
IoT Networks: By incorporating the dynamic encryption scheme, IoT networks can enhance the security of data transmission and processing, safeguarding sensitive information and preventing unauthorized access.
Healthcare Systems: The encryption scheme could be utilized to protect patient data and ensure the secure operation of healthcare systems, maintaining patient privacy and confidentiality.
Autonomous Vehicles: Applying the dynamic encryption scheme can enhance the security of communication and control systems in autonomous vehicles, protecting against cyber-attacks and ensuring safe operation.

By extending the concepts and methodologies from this paper to these diverse cyber-physical systems, it is possible to strengthen their security measures, mitigate potential vulnerabilities, and safeguard critical operations and data.