Physical Authentication of Control Systems: Designing Watermarked Control Inputs to Detect Counterfeit Sensor Outputs

Mo, Yilin; Weerakkody, Sean; Sinopoli, Bruno

doi:10.1109/mcs.2014.2364724

Cited by 389 publications

(94 citation statements)

References 15 publications

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“…More specifically, we focus on the adaptation of physical-layer failure detection mechanisms (e.g., systems for the detection of faults and accidents) to handle, as well as, attacks (e.g., replay and integrity attacks conducted by malicious adversaries). We extend the work proposed in [3] which reexamines the security of a specific scheme proposed by Mo et al in [4,5].…”

Section: Introductionmentioning

confidence: 85%

“…• We reexamine the effectiveness of the attack detector proposed in [4,5] under new adversary models.…”

Section: Contributionsmentioning

confidence: 99%

“…Section 3 reviews the detector scheme in [4,5], and defines our adversary models and reexamines the security of the detector under the new adversary models. Section 4 adapts the detection scheme in [4,5] to handle the uncovered limitations and validates the resulting approach via numerical simulations. Section 5 presents experimental results based on a laboratory testbed.…”

Section: Contributionsmentioning

confidence: 99%

“…This may partially solve the aforementioned problem. Without underestimating cryptographic solutions, in this paper, we consider a complementary solution proposed by Mo et al [4,5] to protect the integrity of the physical sensor measurements by means of authentication watermarks. Such watermarks are enforced by adapting a real-time failure detector based on linear time invariant models of industrial control systems.…”

Section: Networked-control Systems (Ncss)mentioning

confidence: 99%

“…Do et al study in [18] strategies for handling cyber-physical attacks using statistical detection methods. Mo et al propose in [4,5] the use of watermark-based detection by adapting traditional failure detection mechanisms (e.g., detectors to handle faults and errors). In the following sections, we elaborate further on the watermark-based technique by Mo et al discuss about some security limitations and propose an improved technique.…”

Section: Cyber-physical Attacksmentioning

confidence: 99%

See 4 more Smart Citations

On the use of watermark-based schemes to detect cyber-physical attacks

Rubio‐Hernan

Cicco

García-Alfaro

2017

EURASIP J. on Info. Security

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We address security issues in cyber-physical systems (CPSs). We focus on the detection of attacks against cyber-physical systems. Attacks against these systems shall be handled both in terms of safety and security. Networked-control technologies imposed by industrial standards already cover the safety dimension. However, from a security standpoint, using only cyber information to analyze the security of a cyber-physical system is not enough, since the physical malicious actions that can threaten the correct behavior of the systems are ignored. For this reason, the systems have to be protected from threats to their cyber and physical layers. Some authors have handled replay and integrity attacks using, for example, physical attestation to validate the cyber process and to detect the attacks, or watermark-based detectors which uses also physical parameters to ensure the cyber layers. We reexamine the effectiveness of a stationary watermark-based detector. We show that this approach only detects adversaries that do not attempt to get any knowledge about the system dynamics. We analyze the detection ratio of the original design under the presence of new adversaries that are able to infer the system dynamics and are able to evade the detector with high frequency. We propose a new detection scheme which employs several non-stationary watermarks. We validate the detection efficiency of the new strategy via numeric simulations and via running experiments on a laboratory testbed. Results show that the proposed strategy is able to detect adversaries using non-parametric methods, but it is not equally effective against adversaries using parametric identification methods.

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Section: Introductionmentioning

confidence: 85%

“…• We reexamine the effectiveness of the attack detector proposed in [4,5] under new adversary models.…”

Section: Contributionsmentioning

confidence: 99%

Section: Contributionsmentioning

confidence: 99%

Section: Networked-control Systems (Ncss)mentioning

confidence: 99%

Section: Cyber-physical Attacksmentioning

confidence: 99%

See 3 more Smart Citations

On the use of watermark-based schemes to detect cyber-physical attacks

Rubio‐Hernan

Cicco

García-Alfaro

2017

EURASIP J. on Info. Security

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The sensor‐actuators stealthy cyber‐attacks framework on networked control systems: A data‐driven approach

Xin,

Yang,

Long

2023

Asian Journal of Control

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In this study, we address two fundamental questions that are crucial for designing stealthy cyber‐attacks similar to false data injection. The first question involves obtaining an accurate dynamic model of the target to ensure stealthy performance under a detector. The second question pertains to understanding the opponent's ongoing detection tactics, such as dynamic watermarking, and developing a counter‐strategy. To answer the first question, we propose a data‐driven framework that calculates the accurate dynamic model used in stealthy false data injection cyber‐attacks, including zero dynamics attacks, covert attacks, and replay attacks. To address the second question, we present a scheme against the dynamic watermarking defense strategy, which typically detects replay attacks. We validate the methods introduced in this study through an experimental setup of a cyber‐physical system, which includes an omnidirectional mobile robot, a wireless network router, and a remote control center.

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Internet of Things device authentication via electromagnetic fingerprints

Souza

Carlson

Ramos

et al. 2020

Engineering Reports

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We quickly approach a future where Internet of Things (IoT) devices are the norm. In this scenario, humans are surrounded by a multitude of heterogeneous devices that assist them in almost every aspect of their daily routines. The realization of this future demands strong authentication guarantees to ensure that these devices are not abused and that their users are not endangered. However, providing authentication for these systems is challenging due to the high heterogeneity of IoT applications. In this paper, we first review several IoT application scenarios and promising authentication methods for each. We identify th e key characteristics of each IoT application scenario, present the strengths and weaknesses of prominent authentication methods from the literature, and review which authentication methods have been proposed in the literature for each application. Then, we present a novel authentication method for IoT based on electromagnetic noise. The key advantage of electromagnetic noise is that any electronic device intrinsically generates electromagnetic noise during normal operation. We extract features from these electromagnetic emanations and use machine learning algorithms to identify devices based on these features. Our method achieves 77% accuracy when identifying devices among a set of seven devices.

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Physical Authentication of Control Systems: Designing Watermarked Control Inputs to Detect Counterfeit Sensor Outputs

Cited by 389 publications

References 15 publications

On the use of watermark-based schemes to detect cyber-physical attacks

On the use of watermark-based schemes to detect cyber-physical attacks

The sensor‐actuators stealthy cyber‐attacks framework on networked control systems: A data‐driven approach

Internet of Things device authentication via electromagnetic fingerprints

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