The DOI matches its Crossref record.
Attack models and scenarios for networked control systems
Abstract
Cyber-secure networked control is modeled, analyzed, and experimentally illustrated in this paper. An attack space defined by the adversary's system knowledge, disclosure, and disruption resources is introduced. Adversaries constrained by these resources are modeled for a networked control system architecture. It is shown that attack scenarios corresponding to replay, zero dynamics, and bias injection attacks can be analyzed using this framework. An experimental setup based on a quadruple-tank process controlled over a wireless network is used to illustrate the attack scenarios, their consequences, and potential counter-measures.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A survey of physics-based attack detection in cyber-physical systems
Giraldo, J., Urbina, D., Cardenas, A., Valente, J., Faisal, M., Ruths, J., Tippenhauer, N. O., Sandberg, H., & Candell, R. (2019) · ACM Computing Surveys · doi:10.1145/3203245 · Cited by 535
Self-citationSecure Fusion Estimation for Bandwidth Constrained Cyber-Physical Systems Under Replay Attacks
Chen, B., Ho, D. W. C., Hu, G., & Yu, L. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2716115 · Cited by 336
Kravchik, M., & Shabtai, A. (2022) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2021.3050101 · Cited by 224
Anomaly detection for a water treatment system based on one-class neural network
Aboah Boateng, E., Bruce, J. W., & Talbert, D. A. (2022) · IEEE Access · doi:10.1109/access.2022.3218624 · Cited by 44
Metadata
- Authors
- Teixeira, A., Pérez, D., Sandberg, H., & Johansson, K. H.
- Venue
- Proceedings of the 1st international conference on High Confidence Networked Systems
- Publisher
- ACM
- Published
- 2012-04-17
- Pages
- 55-64
- OpenAlex
- W2158469273
- Cited by
- 471
- References
- 0
- FWCI
- 29.35
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Attack models and scenarios for networked control systems. https://app.cochat.ai/papers/10.1145/2185505.2185515
- The paper
- Teixeira, A., Pérez, D., Sandberg, H., & Johansson, K. H. (2012). Attack models and scenarios for networked control systems. Proceedings of the 1st international conference on High Confidence Networked Systems. https://doi.org/10.1145/2185505.2185515
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.