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Teixeira, André, Associate ProfessorORCID iD iconorcid.org/0000-0001-5491-4068
Alternative names
Publications (10 of 59) Show all publications
Tosun, F. E., Teixeira, A., Abdalmoaty, M.-H. R. -., Ahlén, A. & Dey, S. (2024). Quickest detection of bias injection attacks on the glucose sensor in the artificial pancreas under meal disturbances. Journal of Process Control, 135, Article ID 103162.
Open this publication in new window or tab >>Quickest detection of bias injection attacks on the glucose sensor in the artificial pancreas under meal disturbances
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2024 (English)In: Journal of Process Control, ISSN 0959-1524, E-ISSN 1873-2771, Vol. 135, article id 103162Article in journal (Refereed) Published
Abstract [en]

Modern glucose sensors deployed in closed -loop insulin delivery systems, so-called artificial pancreas use wireless communication channels. While this allows a flexible system design, it also introduces vulnerability to cyberattacks. Timely detection and mitigation of attacks are imperative for device safety. However, large unknown meal disturbances are a crucial challenge in determining whether the sensor has been compromised or the sensor glucose trajectories are normal. We address this issue from a control -theoretic security perspective. In particular, a time -varying Kalman filter is employed to handle the sporadic meal intakes. The filter prediction error is then statistically evaluated to detect anomalies if present. We compare two state-of-the-art online anomaly detection algorithms, namely the ᅵᅵᅵᅵᅵᅵ2 and CUSUM tests. We establish a robust optimal detection rule for unknown bias injections. Even if the optimality holds only for the restrictive case of constant bias injections, we show that the proposed model -based anomaly detection scheme is also effective for generic non -stealthy sensor deception attacks through numerical simulations.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Type 1 diabetes mellitus, Artificial pancreas, Quickest change detection, Control-theoretic security, Sensor deception attack
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-525038 (URN)10.1016/j.jprocont.2024.103162 (DOI)001164643000001 ()
Funder
Swedish Research Council, 2018-04396Swedish Foundation for Strategic Research
Available from: 2024-03-27 Created: 2024-03-27 Last updated: 2024-03-27Bibliographically approved
Zhang, Q., Liu, K., Teixeira, A. M. H., Li, Y., Chai, S. & Xia, Y. (2023). An Online Kullback-Leibler Divergence-Based Stealthy Attack Against Cyber-Physical Systems. IEEE Transactions on Automatic Control, 68(6), 3672-3679
Open this publication in new window or tab >>An Online Kullback-Leibler Divergence-Based Stealthy Attack Against Cyber-Physical Systems
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2023 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 68, no 6, p. 3672-3679Article in journal (Refereed) Published
Abstract [en]

This article investigates the design of online stealthy attacks with the aim of moving the system's state to the desired target. Different from the design of offline attacks, which is only based on the system's model, to design the online attack, the attacker also estimates the system's state with the intercepted data at each instant and computes the optimal attack accordingly. To ensure stealthiness, the Kullback-Leibler divergence between the innovations with and without attacks at each instant should be smaller than a threshold. We show that the attacker should solve a convex optimization problem at each instant to compute the mean and covariance of the attack. The feasibility of the attack policy is also discussed. Furthermore, for the strictly stealthy case with zero threshold, the analytical expression of the unique optimal attack is given. Finally, a numerical example of the longitudinal flight control system is adopted to illustrate the effectiveness of the proposed attack.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
Detectors, Technological innovation, Kalman filters, Filtering theory, Symmetric matrices, Sensors, Automation, Kullback-Leibler divergence (KLD), online stealthy attack, security of the cyber-physical systems (CPSs)
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-507478 (URN)10.1109/TAC.2022.3192201 (DOI)000995899800040 ()
Funder
Swedish Research Council, 2018-04396.Swedish Foundation for Strategic Research
Available from: 2023-07-07 Created: 2023-07-07 Last updated: 2023-09-26Bibliographically approved
Wigren, T. & Teixeira, A. (2023). Feedback Path Delay Attacks and Detection. In: Proceedings of the 62nd IEEE Conference on Decision and Control (CDC): . Paper presented at IEEE 62nd IEEE Conference on Decision and Control (CDC), DEC 13-15, 2023, IEEE Control Syst Soc, Singapore, SINGAPORE (pp. 3864-3871). Singapore: Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Feedback Path Delay Attacks and Detection
2023 (English)In: Proceedings of the 62nd IEEE Conference on Decision and Control (CDC), Singapore: Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 3864-3871Conference paper, Published paper (Refereed)
Abstract [en]

The paper discusses delay injection attacks on regulator loops and suggests joint recursive prediction error identification of delay and dynamics for supervision and attack detection. The control system is assumed to be operated either in open- or closed-loop mode. It is shown why delay insertion in the feedback path before the user switches to closed-loop operation is advantageous to disguise the attack. The detection performance is evaluated numerically for a linearized automotive cruise control feedback loop.

Place, publisher, year, edition, pages
Singapore: Institute of Electrical and Electronics Engineers (IEEE), 2023
Series
Proceedings / IEEE Conference on Decision and Control, ISSN 0743-1546, E-ISSN 2576-2370
National Category
Control Engineering
Research subject
Automatic Control
Identifiers
urn:nbn:se:uu:diva-518632 (URN)10.1109/CDC49753.2023.10383217 (DOI)001166433803033 ()979-8-3503-0124-3 (ISBN)979-8-3503-0125-0 (ISBN)
Conference
IEEE 62nd IEEE Conference on Decision and Control (CDC), DEC 13-15, 2023, IEEE Control Syst Soc, Singapore, SINGAPORE
Funder
Swedish Foundation for Strategic Research
Available from: 2023-12-21 Created: 2023-12-21 Last updated: 2024-03-25Bibliographically approved
Ramos, G., Teixeira, A. & Pequito, S. (2023). On the trade-offs between accuracy, privacy, and resilience in average consensus algorithms. In: 2023 62nd IEEE Conference on Decision and Control, (CDC): . Paper presented at 62nd IEEE Conference on Decision and Control (CDC), DEC 13-15, 2023, IEEE Control Syst Soc, Singapore, SINGAPORE (pp. 8026-8031). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>On the trade-offs between accuracy, privacy, and resilience in average consensus algorithms
2023 (English)In: 2023 62nd IEEE Conference on Decision and Control, (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 8026-8031Conference paper, Published paper (Refereed)
Abstract [en]

There can be none. In this paper, we address the problem of a set of discrete-time networked agents reaching average consensus privately and resiliently in the presence of a subset of attacked agents. Existing approaches to the problem rely on trade-offs between accuracy, privacy, and resilience, sacrificing one for the others. We show that a separation-like principle for privacy-preserving and resilient discrete-time average consensus is possible. Specifically, we propose a scheme that combines strategies from resilient average consensus and private average consensus, which yields both desired properties. The proposed scheme has polynomial time-complexity on the number of agents and the maximum number of attacked agents. In other words, each agent that is not under attack is able to detect and discard the values of the attacked agents, reaching the average consensus of non-attacked agents while keeping each agent's initial state private. Finally, we demonstrate the effectiveness of the proposed method with numerical results.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Series
IEEE Conference on Decision and Control, ISSN 0743-1546, E-ISSN 2576-2370
National Category
Control Engineering Computer Sciences Signal Processing
Identifiers
urn:nbn:se:uu:diva-525498 (URN)10.1109/CDC49753.2023.10383286 (DOI)001166433806095 ()979-8-3503-0124-3 (ISBN)979-8-3503-0125-0 (ISBN)
Conference
62nd IEEE Conference on Decision and Control (CDC), DEC 13-15, 2023, IEEE Control Syst Soc, Singapore, SINGAPORE
Available from: 2024-03-22 Created: 2024-03-22 Last updated: 2024-03-22Bibliographically approved
Wigren, T. & Teixeira, A. (2023). On-line Identification of Delay Attacks in Networked Servo Control. In: IFAC (Ed.), Prep. IFAC World Congress: . Paper presented at 22nd IFAC World Congress (pp. 1041-1047). IFAC Papers Online
Open this publication in new window or tab >>On-line Identification of Delay Attacks in Networked Servo Control
2023 (English)In: Prep. IFAC World Congress / [ed] IFAC, IFAC Papers Online, 2023, p. 1041-1047Conference paper, Published paper (Refereed)
Abstract [en]

The paper discusses attacks on networked control loops by increased delay, and shows how existing round trip jitter may disguise such attacks. The attackers objective need not be de-stabilization, the paper argues that making settling time requirements fail can be sufficient. To defend against such attacks, the paper proposes the use of joint recursive prediction error identification of the round trip delay and the networked closed loop dynamics. The proposed identification algorithm allows general defense, since it is designed for delayed nonlinear dynamics in state space form. Simulations show that the method is able to detect a delay attack on a printed circuit board component mounting servo loop, long before the attack reaches full effect.

Place, publisher, year, edition, pages
IFAC Papers Online, 2023
Keywords
Cyber security, Delay, Detection, Jitter, Nonlinear systems
National Category
Control Engineering
Research subject
Automatic Control
Identifiers
urn:nbn:se:uu:diva-516012 (URN)
Conference
22nd IFAC World Congress
Funder
Swedish Foundation for Strategic Research
Available from: 2023-11-16 Created: 2023-11-16 Last updated: 2023-12-24Bibliographically approved
Nguyen, A. T., Coimbatore Anand, S., Teixeira, A. & Medvedev, A. (2023). Optimal Detector Placement in Networked Control Systems under Cyber-attacks with Applications to Power Networks. In: : . Paper presented at 22nd IFAC World Congress: Yokohama, Japan, July 9-14, 2023 (pp. 1820-1826). Elsevier
Open this publication in new window or tab >>Optimal Detector Placement in Networked Control Systems under Cyber-attacks with Applications to Power Networks
2023 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a game-theoretic method to address the problem of optimal detector placement in a networked control system under cyber-attacks. The networked control system is composed of interconnected agents where each agent is regulated by its local controller over unprotected communication, which leaves the system vulnerable to malicious cyber-attacks. To guarantee a given local performance, the defender optimally selects a single agent on which to place a detector at its local controller with the purpose of detecting cyber-attacks. On the other hand, an adversary optimally chooses a single agent on which to conduct a cyber-attack on its input with the aim of maximally worsening the local performance while remaining stealthy to the defender. First, we present a necessary and sufficient condition to ensure that the maximal attack impact on the local performance is bounded, which restricts the possible actions of the defender to a subset of available agents. Then, by considering the maximal attack impact on the local performance as a game payoff, we cast the problem of finding optimal actions of the defender and the adversary as a zero-sum game. Finally, with the possible action sets of the defender and the adversary, an algorithm is devoted to determining the Nash equilibria of the zero-sum game that yield the optimal detector placement. The proposed method is illustrated on an IEEE benchmark for power systems.

Place, publisher, year, edition, pages
Elsevier, 2023
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-518875 (URN)10.1016/j.ifacol.2023.10.1896 (DOI)
Conference
22nd IFAC World Congress: Yokohama, Japan, July 9-14, 2023
Available from: 2023-12-27 Created: 2023-12-27 Last updated: 2024-01-10Bibliographically approved
Abdalmoaty, M., Coimbatore Anand, S. & Teixeira, A. (2023). Privacy and Security in Network Controlled Systems via Dynamic Masking. Paper presented at 22nd IFAC World Congress, Yokohama, Japan, July 9-14, 2023. IFAC-PapersOnLine, 56(2), 991-996
Open this publication in new window or tab >>Privacy and Security in Network Controlled Systems via Dynamic Masking
2023 (English)In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 56, no 2, p. 991-996Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose a new architecture to enhance the privacy and security of networked control systems against malicious adversaries. We consider an adversary which first learns the system using system identification techniques (privacy), and then performs a data injection attack (security). In particular, we consider an adversary conducting zero-dynamics attacks (ZDA) which maximizes the performance cost of the system whilst staying undetected. Using the proposed architecture, we show that it is possible to (i) introduce significant bias in the system estimates obtained by the adversary: thus providing privacy, and (ii) efficiently detect attacks when the adversary performs a ZDA using the identified system: thus providing security. Through numerical simulations, we illustrate the efficacy of the proposed architecture

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
Networked systems, Secure networked control systems, Linear systems, Privacy
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-525721 (URN)10.1016/j.ifacol.2023.10.1694 (DOI)001196708400157 ()
Conference
22nd IFAC World Congress, Yokohama, Japan, July 9-14, 2023
Funder
Swedish Research Council, 2018-04396Swedish Foundation for Strategic Research
Available from: 2024-03-27 Created: 2024-03-27 Last updated: 2024-04-18Bibliographically approved
Chockalingam, S., Pieters, W., Teixeira, A. & van Gelder, P. (2023). Probability elicitation for Bayesian networks to distinguish between intentional attacks and accidental technical failures. Journal of Information Security and Applications, 75, Article ID 103497.
Open this publication in new window or tab >>Probability elicitation for Bayesian networks to distinguish between intentional attacks and accidental technical failures
2023 (English)In: Journal of Information Security and Applications, ISSN 2214-2134, E-ISSN 2214-2126, Vol. 75, article id 103497Article in journal (Refereed) Published
Abstract [en]

Both intentional attacks and accidental technical failures can lead to abnormal behaviour in components of industrial control systems. In our previous work, we developed a framework for constructing Bayesian Network (BN) models to enable operators to distinguish between those two classes, including knowledge elicitation to construct the directed acyclic graph of BN models. In this paper, we add a systematic method for knowledge elicitation to construct the Conditional Probability Tables (CPTs) of BN models, thereby completing a holistic framework to distinguish between attacks and technical failures. In order to elicit reliable probabilities from experts, we need to reduce the workload of experts in probability elicitation by reducing the number of conditional probabilities to elicit and facilitating individual probability entry. We utilise DeMorgan models to reduce the number of conditional probabilities to elicit as they are suitable for modelling opposing influences i.e., combinations of influences that promote and inhibit the child event. To facilitate individual probability entry, we use probability scales with numerical and verbal anchors. We demonstrate the proposed approach using an example from the water management domain.

Place, publisher, year, edition, pages
ELSEVIER, 2023
Keywords
Bayesian network, DeMorgan model, Intentional attack, Probability elicitation, Technical failure
National Category
Other Civil Engineering
Identifiers
urn:nbn:se:uu:diva-503205 (URN)10.1016/j.jisa.2023.103497 (DOI)000983586700001 ()
Available from: 2023-06-30 Created: 2023-06-30 Last updated: 2023-06-30Bibliographically approved
Naha, A., Teixeira, A., Ahlén, A. & Dey, S. (2023). Quickest detection of deception attacks on cyber-physical systems with a parsimonious watermarking policy. Automatica, 155, Article ID 111147.
Open this publication in new window or tab >>Quickest detection of deception attacks on cyber-physical systems with a parsimonious watermarking policy
2023 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 155, article id 111147Article in journal (Refereed) Published
Abstract [en]

Adding a physical watermarking signal to the control input of a networked control system increases the detection probability of data deception attacks at the expense of increased control cost. This paper proposes a parsimonious policy to limit the average number of watermarking events when the attack is not present, which in turn reduces the control cost. We model the system as a stochastic optimal control problem and apply dynamic programming to minimize the average detection delay (ADD) for fixed upper bounds on false alarm rate (FAR) and an average number of watermarking events (ANW) before the attack. Under practical circumstances, the optimal solution results in a two threshold policy on the posterior probability of attack, derived from the Shiryaev statistics for sequential change detection and assuming the change point is a random variable. We derive asymptotically approximate analytical expressions of ADD and FAR, applying the non-linear renewal theory for non-independent and identically distributed data. The derived expressions reveal that ADD reduces with the increase in the Kullback-Leibler divergence (KLD) between the post-and pre-attack distributions of the test statistics. Therefore, we further design the optimal watermarking that maximizes the KLD for a fixed increase in the control cost. The relationship between the ANW and the increase in control cost is also derived. Simulation studies are performed to illustrate and validate the theoretical results.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Attack detection, Cyber-physical system, Deception attack, Kullback-Leibler divergence, Linear quadratic Gaussian control, Networked control system, Physical watermarking, Sequential change detection in Bayesian, setting, Shiryaev statistics
National Category
Control Engineering Telecommunications
Identifiers
urn:nbn:se:uu:diva-508865 (URN)10.1016/j.automatica.2023.111147 (DOI)001030023500001 ()
Funder
Swedish Research Council, 2017-04053Swedish Research Council, 2018-04396Swedish Foundation for Strategic Research
Available from: 2023-08-11 Created: 2023-08-11 Last updated: 2023-08-11Bibliographically approved
Naha, A., Teixeira, A., Ahlén, A. & Dey, S. (2023). Quickest physical watermarking-based detection of measurement replacement attacks in networked control systems. European Journal of Control, 71, Article ID 100804.
Open this publication in new window or tab >>Quickest physical watermarking-based detection of measurement replacement attacks in networked control systems
2023 (English)In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 71, article id 100804Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose and analyze an attack detection scheme for securing the physical layer of a networked control system (NCS) with a wireless sensor network against attacks where the adversary replaces the true observations with stationary false data. An independent and identically distributed watermarking signal is added to the optimal linear quadratic Gaussian (LQG) control inputs, and a cumulative sum (CUSUM) test is carried out using the joint distribution of the innovation signal and the watermarking signal for quickest attack detection. We derive the expressions of the supremum of the average detection delay (SADD) for a multi-input and multi-output (MIMO) system under the optimal and sub-optimal CUSUM tests. The SADD is asymptotically inversely proportional to the expected Kullback–Leibler divergence (KLD) under certain conditions. The expressions for the MIMO case are simplified for multi-input and single-output systems and explored further to distil design insights. We provide insights into the design of an optimal watermarking signal to maximize KLD for a given fixed increase in LQG control cost when there is no attack. Furthermore, we investigate how the attacker and the control system designer can accomplish their respective objectives by changing the relative power of the attack signal and the watermarking signal. Simulations and numerical studies are carried out to validate the theoretical results.

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
CUSUM test, Cyber-physical system, Deception attack, Linear quadratic gaussian control, Networked control system, Physical watermarking
National Category
Control Engineering Telecommunications Signal Processing
Identifiers
urn:nbn:se:uu:diva-503095 (URN)10.1016/j.ejcon.2023.100804 (DOI)000983436300001 ()
Funder
Swedish Research Council, 2017-04053Swedish Research Council, 2018-04396Swedish Foundation for Strategic Research
Available from: 2023-06-09 Created: 2023-06-09 Last updated: 2023-06-09Bibliographically approved
Projects
Analysis and design of secure and resilient control systems [2018-04396_VR]; Uppsala University; Publications
Tosun, F. E., Teixeira, A., Abdalmoaty, M.-H. R. -., Ahlén, A. & Dey, S. (2024). Quickest detection of bias injection attacks on the glucose sensor in the artificial pancreas under meal disturbances. Journal of Process Control, 135, Article ID 103162.
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ORCID iD: ORCID iD iconorcid.org/0000-0001-5491-4068

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