# Publications

1. P. Hespanhol, M. Porter, R. Vasudevan, A. Aswani, "Sensor Switching Control Under Attacks Detectable by Finite Sample Dynamic Watermarking Tests," IEEE Transactions on Automatic Control (TAC), 2021.

[preprint] [] []

Control system security is enhanced by the ability to detect malicious attacks on sensor measurements. Dynamic watermarking can detect such attacks on linear time-invariant (LTI) systems. However, existing theory focuses on attack detection and not on the use of watermarking in conjunction with attack mitigation strategies. In this paper, we study the problem of switching between two sets of sensors: One set of sensors has high accuracy but is vulnerable to attack, while the second set of sensors has low accuracy but cannot be attacked. The problem is to design a sensor switching strategy based on attack detection by dynamic watermarking. This requires new theory because existing results are not adequate to control or bound the behavior of sensor switching strategies that use finite data. To overcome this, we develop new finite sample hypothesis tests for dynamic watermarking in the case of bounded disturbances, using the modern theory of concentration of measure for random matrices. Our resulting switching strategy is validated with a simulation analysis in an autonomous driving setting, which demonstrates the strong performance of our proposed policy.
@article{hespanhol2021sensor,
title={Sensor Switching Control Under Attacks Detectable by Finite Sample Dynamic Watermarking Tests},
author={Hespanhol, Pedro and Porter, Matthew and Vasudevan, Ram and Aswani, Anil},
journal={IEEE Transactions on Automatic Control (TAC)},
year={2020},
note={To Appear}
}

2. M. Porter, P. Hespanhol, A. Aswani, M. Johnson-Roberson, R. Vasudevan, "Detecting Generalized Replay Attacks via Time-Varying Dynamic Watermarking," IEEE Transactions on Automatic Control (TAC), 2021.

[preprint] [] []

Cyber-physical systems (CPS) often rely on external communication for supervisory control or sensing. Unfortunately, these communications render the system vulnerable to cyber-attacks. Attacks that alter messages, such as replay attacks that record measurement signals and then play them back to the system, can cause devastating effects. Dynamic Watermarking methods, which inject a private excitation into control inputs to secure resulting measurement signals, have begun addressing the challenges of detecting these attacks, but have been restricted to linear time invariant (LTI) systems. Though LTI models are sufficient for some applications, other CPS, such as autonomous vehicles, require more complex models. This paper develops a linear time-varying (LTV) extension to previous Dynamic Watermarking methods by designing a matrix normalization factor to accommodate the temporal changes in the system. Implementable tests are provided with considerations for real-world systems. The proposed method is then shown to be able to detect generalized replay attacks both in theory and in simulation using a LTV vehicle model.
@article{porter2021ltv,
title={Detecting Generalized Replay Attacks via Time-Varying Dynamic Watermarking},
author={Porter, Matthew and Hespanhol, Pedro and Aswani, Anil and Johnson-Roberson, Matthew and Vasudevan, Ram},
journal={IEEE Transactions on Automatic Control (TAC)},
year={2020},
note={To Appear}
}

3. M. Olfat, S. Sloan, P. Hespanhol, M. Porter, R. Vasudevan, A. Aswani, "Covariance-Robust Dynamic Watermarking," 2020 IEEE 59th Annual Conference on Decision and Control (CDC), 2020.

[preprint] [] []

Attack detection and mitigation strategies for cyberphysical systems (CPS) are an active area of research, and researchers have developed a variety of attack-detection tools such as dynamic watermarking. However, such methods often make assumptions that are difficult to guarantee, such as exact knowledge of the distribution of measurement noise. Here, we develop a new dynamic watermarking method that we call covariance-robust dynamic watermarking, which is able to handle uncertainties in the covariance of measurement noise. Specifically, we consider two cases. In the first this covariance is fixed but unknown, and in the second this covariance is slowly-varying. For our tests, we only require knowledge of a set within which the covariance lies. Furthermore, we connect this problem to that of algorithmic fairness and the nascent field of fair hypothesis testing, and we show that our tests satisfy some notions of fairness. Finally, we exhibit the efficacy of our tests on empirical examples chosen to reflect values observed in a standard simulation model of autonomous vehicles.
@inproceedings{olfat2020robust,
title={Covariance-Robust Dynamic Watermarking},
author={Olfat, Matthew and Sloan, Stephen and Hespanhol, Pedro and Porter, Matthew and Vasudevan, Ram and Aswani, Anil},
booktitle={2020 IEEE 59th Annual Conference on Decision and Control (CDC)},
year={2020},
note={To Appear}
}

4. M. Porter, S. Dey, A. Joshi, P. Hespanhol, A. Aswani, M. Johnson-Roberson, R. Vasudevan, "Detecting Deception Attacks on Autonomous Vehicles via Linear Time-Varying Dynamic Watermarking," 2020 IEEE Conference on Control Technology and Applications (CCTA), 2020.

[preprint] [] []

Cyber-physical systems (CPS) such as autonomous vehicles rely on both on-board sensors and external communications to estimate their state. Unfortunately, these communications render the system vulnerable to cyber-attacks. While many attack detection methods have begun to address these concerns, they are limited to linear time-invariant (LTI) systems. Though LTI system models provide accurate approximations for CPS such as autonomous vehicles at constant speed and turning radii, they are inaccurate for more complex motions such as lane changes, turns, and changes in velocity. Since these more complex motions are more suitably described by linear time-varying (LTV) system models rather than LTI models, Dynamic Watermarking, which adds a private excitation to the input signal to validate measurements, has recently been extended to LTV systems. However, this extension does not allow for LTV systems that require several steps before the effect of a given control input can be seen in the measurement signal. Additionally, there is no consideration for the time-varying effects of auto-correlation. Furthermore, a proof of concept was only provided using simulations of a simplified model.
This paper relaxes the requirement for inputs to be visible in a single step and constructs an auto-correlation normalizing factor to remove the effects of auto-correlation. In addition, Dynamic Watermarking is applied to a high-fidelity vehicle model in carsim and a 1/10 scale autonomous rover to further reinforce the proof of concept for realistic systems. In each case, the vehicle follows a predefined path with time-varying velocity and turning radii. A replay attack, which replays previously recorded measurements, is shown to be detectable using LTV Dynamic Watermarking in a quick and repeatable manner.
@inproceedings{porter2020deception,
title={Detecting Deception Attacks on Autonomous Vehicles via Linear Time-Varying Dynamic Watermarking},
author={Porter, Matthew and Dey, Sidhartha and Joshi, Arnav and Hespanhol, Pedro and Aswani, Anil and Johnson-Roberson, Matthew and Vasudevan, Ram},
booktitle={2020 IEEE Conference on Control Technology and Applications (CCTA)},
pages={969--976},
doi={},
year={2020},
organization={IEEE}
}

5. M. Porter, A. Joshi, P. Hespanhol, A. Aswani, M. Johnson-Roberson, R. Vasudevan, "Simulation and Real-World Evaluation of Attack Detection Schemes," in 2019 Annual American Control Conference (ACC), 2019.

[tech-report] [video] [] []

A variety of anomaly detection schemes have been proposed to detect malicious attacks to Cyber-Physical Systems. Among these schemes, Dynamic Watermarking methods have been proven highly effective at detecting a wide range of attacks. Unfortunately, in contrast to other anomaly detectors, no method has been presented to design a Dynamic Watermarking detector to achieve a user-specified false alarm rate, or subsequently evaluate the capabilities of an attacker under such a selection. This paper describes methods to measure the capability of an attacker, to numerically approximate this metric, and to design a Dynamic Watermarking detector that can achieve a user-specified rate of false alarms. The performance of the Dynamic Watermarking detector is compared to three classical anomaly detectors in simulation and on a real-world platform. These experiments illustrate that the attack capability under the Dynamic Watermarking detector is comparable to those of classic anomaly detectors. Importantly, these experiments also make clear that the Dynamic Watermarking detector is consistently able to detect attacks that the other class of detectors are unable to identify.
@inproceedings{porter2019simulation,
title={Simulation and real-world evaluation of attack detection schemes},
author={Porter, Matthew and Joshi, Arnav and  Hespanhol, Pedro and Aswani, Anil and Johnson-Roberson, Matthew and  Vasudevan, Ram},
booktitle={2019 Annual American Control Conference (ACC)},
pages={551--558},
doi={10.23919/ACC.2019.8815318},
year={2019},
organization={IEEE}
}

6. P. Hespanhol, M. Porter, R. Vasudevan, A. Aswani, "Statistical Watermarking for Networked Control Systems," in 2018 Annual American Control Conference (ACC), 2018.

[preprint] [] []

Watermarking can detect sensor attacks in control systems by injecting a private signal into the control, whereby attacks are identified by checking the statistics of the sensor measurements and private signal. However, past approaches assume full state measurements or a centralized controller, which is not found in networked LTI systems with subcontrollers. Since generally the entire system is neither controllable nor observable by a single subcontroller, communication of sensor measurements is required to ensure closed-loop stability. The possibility of attacking the communication channel has not been explicitly considered by previous watermarking schemes, and requires a new design. In this paper, we derive a statistical watermarking test that can detect both sensor and communication attacks. A unique (compared to the non-networked case) aspect of the implementing this test is the state-feedback controller must be designed so that the closed-loop system is controllable by each sub-controller, and we provide two approaches to design such a controller using Heymann's lemma and a multi-input generalization of Heymann's lemma. The usefulness of our approach is demonstrated with a simulation of detecting attacks in a platoon of autonomous vehicles. Our test allows each vehicle to independently detect attacks on both the communication channel between vehicles and on the sensor measurements.
@inproceedings{hespanhol2018statistical,
title={Statistical watermarking for networked control systems},
author={Hespanhol, Pedro and Porter, Matthew and Vasudevan, Ram and Aswani, Anil},
booktitle={2018 Annual American Control Conference (ACC)},
pages={5467-5472},
doi={10.23919/ACC.2018.8431569},
year={2018},
organization={IEEE}
}

7. P. Hespanhol, M. Porter, R. Vasudevan, A. Aswani, "Dynamic Watermarking for General LTI Systems," in 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2017.

[preprint] [] []

Detecting attacks in control systems is an important aspect of designing secure and resilient control systems. Recently, a dynamic watermarking approach was proposed for detecting malicious sensor attacks for SISO LTI systems with partial state observations and MIMO LTI systems with a full rank input matrix and full state observations; however, these previous approaches cannot be applied to general LTI systems that are MIMO and have partial state observations. This paper designs a dynamic watermarking approach for detecting malicious sensor attacks for general LTI systems, and we provide a new set of asymptotic and statistical tests. We prove these tests can detect attacks that follow a specified attack model (more general than replay attacks), and we also show that these tests simplify to existing tests when the system is SISO or has full rank input matrix and full state observations. The benefit of our approach is demonstrated with a simulation analysis of detecting sensor attacks in autonomous vehicles. Our approach can distinguish between sensor attacks and wind disturbance (through an internal model principle framework), whereas improperly designed tests cannot distinguish between sensor attacks and wind disturbance.
@inproceedings{hespanhol2017dynamic,
title={Dynamic watermarking for general LTI systems},
author={Hespanhol, Pedro and Porter, Matthew and Vasudevan, Ram and Aswani, Anil},
booktitle={2017 IEEE 56th Annual Conference on Decision and Control (CDC)},
pages={1834-1839},
doi={10.1109/CDC.2017.8263914},
year={2017},
organization={IEEE}
}

8. M. Porter, V. Raghavan, Y. Lin, Z.M. Mao, K. Barton, D. Tilbury, "Production as a Service: Optimizing Utilization in Manufacturing Systems," in ASME Dynamic Systems and Control Conference (DSCC), 2016.

[] []

While advances in technology have greatly improved the process of mass production, producing small batches or one-offs in an efficient manner has remained challenging for the manufacturing industry. Additionally, in both large and small companies, there are often available manufacturing resources that sit idle between projects. In this paper we present a Production as a Service framework for providing manufacturing options to designers of new products based on available manufacturing resources. The designed framework aims to bridge the gap between the theoretical work that has been done on Service Oriented Architectures in manufacturing, and what is required for implementation. An industrial use case is provided as an example of the framework.
@inproceedings{porter2016production,
title={Production as a service: Optimizing utilization in manufacturing systems},
author={Porter, Matthew and Raghavan, Vikram and Lin, Yikai and Mao, Z Morley and Barton, Kira and Tilbury, Dawn},
booktitle={ASME 2016 Dynamic Systems and Control Conference (DSCC)},
pages={V002T21A012--V002T21A012},
doi={10.1115/DSCC2016-9908},
year={2016},
organization={American Society of Mechanical Engineers}
}