A survey of physics-based attack detection in cyber-physical systems
Open accessAbstract
Monitoring the "physics" of cyber-physical systems to detect attacks is a growing area of research. In its basic form a security monitor creates time-series models of sensor readings for an industrial control system and identifies anomalies in these measurements in order to identify potentially false control commands or false sensor readings. In this paper, we review previous work on physics-based anomaly detection based on a unified taxonomy that allows us to identify limitations and unexplored challenges, and propose new solutions.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The focus of most of the surveys for CPS is on security and privacy.
“The focus of most of the surveys for CPS is on security and privacy (e.g., [84,85,93,96,102,112,113,119,124]).”
From A Systematic Review of Data Quality in CPS and IoT for Industry 4.0 (2023) · cites this paper as [85]
The Related Work section describes numerous CPS surveys addressing security and privacy, including surveys of smart grids and general CPS. It does not establish that these make up most CPS surveys, so the claim's majority assertion is unsupported. (LLM, conf=0.83)
Experimental — accuracy not yet measuredIoT devices and networks are highly vulnerable to security attacks that target data integrity and service availability.
“Unfortunately, IoT devices and networks are known to be highly vulnerable to security attacks that target data integrity and service availability.”
From Deep learning-enabled anomaly detection for IoT systems (2023) · cites this paper as [6]
The Introduction (§1.1; page unavailable) says an attacker controlling a sensor, actuator, or controller can send manipulated values, supporting the data-integrity concern for cyber-physical systems. The copy does not establish that IoT devices and networks generally are highly vulnerable, or that the attacks target service availability. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
False data injection attacks against state estimation in electric power grids
Liu, Y., Ning, P., & Reiter, M. K. (2011) · ACM Transactions on Information and System Security · doi:10.1145/1952982.1952995 · Cited by 2,469 · see citing works
A survey of design methods for failure detection in dynamic systems
Willsky, A. S. (1976) · Automatica · doi:10.1016/0005-1098(76)90041-8 · Cited by 2,153 · see citing works
Attack Detection and Identification in Cyber-Physical Systems
Pasqualetti, F., Dörfler, F., & Bullo, F. (2013) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2013.2266831 · Cited by 2,139 · see citing works
Stuxnet: Dissecting a cyberwarfare weapon
Langner, R. (2011) · IEEE Security & Privacy Magazine · doi:10.1109/msp.2011.67 · Cited by 1,922 · see citing works
Experimental Security Analysis of a Modern Automobile
Koscher, K., Czeskis, A., Roesner, F., Patel, S., Kohno, T., Checkoway, S., McCoy, D., Kantor, B., Anderson, D., Shacham, H., et al. (2010) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp.2010.34 · Cited by 1,897 · see citing works
System identification—A survey
Åström, K. J., & Eykhoff, P. (1971) · Automatica · doi:10.1016/0005-1098(71)90059-8 · Cited by 1,506 · see citing works
False data injection attacks against state estimation in electric power grids
Liu, Y., Ning, P., & Reiter, M. K. (2009) · Proceedings of the ACM Conference on Computer and Communications Security · doi:10.1145/1653662.1653666 · Cited by 1,315 · see citing works
A Survey of Fault Detection, Isolation, and Reconfiguration Methods
Hwang, I., Kim, S., Kim, Y., & Seah, C. E. (2009) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2009.2026285 · Cited by 1,308 · see citing works
Sontag, E. D. (1998) · Texts in applied mathematics · doi:10.1007/978-1-4612-0577-7 · Cited by 1,227 · see citing works
Survey of model-based failure detection and isolation in complex plants
Gertler, J. J. (1988) · IEEE Control Systems Magazine · doi:10.1109/37.9163 · Cited by 1,117 · see citing works
The quadruple-tank process: a multivariable laboratory process with an adjustable zero
Johansson, K. H. (2000) · IEEE Transactions on Control Systems Technology · doi:10.1109/87.845876 · Cited by 1,108 · see citing works
Levine, W. S. (2005) · Cited by 1,064 · see citing works
Secure control against replay attacks
Mo, Y., & Sinopoli, B. (2009) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton.2009.5394956 · Cited by 921 · see citing works
A survey of intrusion detection techniques for cyber-physical systems
Mitchell, R., & Chen, I.-R. (2014) · ACM Computing Surveys · doi:10.1145/2542049 · Cited by 768 · see citing works
Shokri, R., Theodorakopoulos, G., Boudec, J. L., & Hubaux, J. (2011) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp.2011.18 · Cited by 711 · see citing works
Unmanned Aircraft Capture and Control Via GPS Spoofing
Kerns, A. J., Shepard, D. P., Bhatti, J., & Humphreys, T. (2014) · J. Field Robotics · doi:10.1002/rob.21513 · Cited by 709 · see citing works
Attacks against process control systems: risk assessment, detection, and response
Cárdenas, A. A., Amin, S., Lin, Z.-S., Huang, Y.-L., Huang, C.-Y., & Sastry, S. (2011) · Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security · doi:10.1145/1966913.1966959 · Cited by 699 · see citing works
Detecting Integrity Attacks on SCADA Systems
Mo, Y., Chabukswar, R., & Sinopoli, B. (2013) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2013.2280899 · Cited by 643 · see citing works
The base-rate fallacy and the difficulty of intrusion detection
Axelsson, S. (2000) · ACM Transactions on Information and System Security · doi:10.1145/357830.357849 · Cited by 640 · see citing works
Proceedings of 1994 American Control Conference - ACC '94
(1994) · doi:10.1109/acc.1994 · Cited by 633 · see citing works
The Purdue enterprise reference architecture
Williams, T. J. (1994) · Computers in Industry · doi:10.1016/0166-3615(94)90017-5 · Cited by 632 · see citing works
Cyber Security and Privacy Issues in Smart Grids
Liu, J., Xiao, Y., Li, S., Liang, W. G., & Chen, C. L. P. (2012) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2011.122111.00145 · Cited by 586 · see citing works
Strategic Protection Against Data Injection Attacks on Power Grids
Kim, T. T., & Poor, H. V. (2011) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2119336 · Cited by 584 · see citing works
Survey in Smart Grid and Smart Home Security: Issues, Challenges and Countermeasures
Komninos, N., Philippou, E., & Pitsillides, A. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2014.2320093 · Cited by 565 · see citing works
Mo, Y., Weerakkody, S., & Sinopoli, B. (2015) · IEEE Control Systems · doi:10.1109/mcs.2014.2364724 · Cited by 508 · see citing works
Attack models and scenarios for networked control systems
Teixeira, A. M. H., Perez, D. V., Sandberg, H., & Johansson, K. H. (2012) · International Conference on High Confidence Networked Systems · doi:10.1145/2185505.2185515 · Cited by 492 · see citing works
Self-citationModel-Based Attack Detection and Mitigation for Automatic Generation Control
Sridhar, S., & Govindarasu, M. (2014) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2014.2298195 · Cited by 488 · see citing works
Cyber‐physical attacks and defences in the smart grid: a survey
He, H., & Yan, J. (2016) · IET Cyber-Physical Systems Theory & Applications · doi:10.1049/iet-cps.2016.0019 · Cited by 457 · see citing works
Detecting False Data Injection Attacks on DC State Estimation
Bobba, R. B., Rogers, K. M., Wang, Q., Khurana, H., Nahrstedt, K., & Overbye, T. J. (2010) · Cited by 448 · see citing works
Stealth Attacks and Protection Schemes for State Estimators in Power Systems
Dán, G., & Sandberg, H. (2010) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgrid.2010.5622046 · Cited by 433 · see citing works
Self-citationA Survey on Smart Grid Cyber-Physical System Testbeds
Cintuglu, M. H., Mohammed, O. A., Akkaya, K., & Uluagac, A. S. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2627399 · Cited by 424 · see citing works
Cyber security analysis of state estimators in electric power systems
Teixeira, A. M. H., Amin, S., Sandberg, H., Johansson, K. H., & Sastry, S. (2010) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2010.5717318 · Cited by 411 · see citing works
Self-citationLimiting the Impact of Stealthy Attacks on Industrial Control Systems
Urbina, D. I., Giraldo, J., Cárdenas, Á. A., Tippenhauer, N. O., Valente, J., Faisal, M. A., Ruths, J., Candell, R., & Sandberg, H. (2016) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/2976749.2978388 · Cited by 360 · see citing works
Self-citationVirtual trip lines for distributed privacy-preserving traffic monitoring
Hoh, B., Gruteser, M., Herring, R., Ban, J. X., Work, D. B., Herrera, J. C., Bayen, A. M., Annavaram, M., & Jacobson, Q. A. (2008) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/1378600.1378604 · Cited by 355 · see citing works
Malicious Data Attacks on Smart Grid State Estimation: Attack Strategies and Countermeasures
Kosut, O., Jia, L., Thomas, R. J., & Tong, L. (2010) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgrid.2010.5622045 · Cited by 352 · see citing works
Amin, S., Litrico, X., Sastry, S., & Bayen, A. M. (2012) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2012.2211873 · Cited by 350 · see citing works
On Security Indices for State Estimators in Power Networks
Sandberg, H., Teixeira, A. M. H., & Johansson, K. H. (2010) · Cited by 322 · see citing works
Self-citationUsing Model-based Intrusion Detection for SCADA Networks
Cheung, S. W., Dutertre, B., Fong, M. W., Lindqvist, U., Skinner, K., & Valdes, A. (2006) · Cited by 321 · see citing works
Revealing stealthy attacks in control systems
Teixeira, A. M. H., Shames, I., Sandberg, H., & Johansson, K. (2012) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton.2012.6483441 · Cited by 298 · see citing works
Self-citationSecurity analysis for Cyber-Physical Systems against stealthy deception attacks
Kwon, C., Liu, W., & Hwang, I. (2013) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2013.6580348 · Cited by 295 · see citing works
Covert Misappropriation of Networked Control Systems: Presenting a Feedback Structure
Smith, R. S. (2015) · IEEE Control Systems · doi:10.1109/mcs.2014.2364723 · Cited by 269 · see citing works
Survey of Security Advances in Smart Grid: A Data Driven Approach
Tan, S., De, D., Song, W., Yang, J., & Das, S. K. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2616442 · Cited by 266 · see citing works
A Multidimensional Critical State Analysis for Detecting Intrusions in SCADA Systems
Carcano, A., Coletta, A., Guglielmi, M., Masera, M., Nai Fovino, I., & Trombetta, A. (2011) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2010.2099234 · Cited by 259 · see citing works
SoK: Security and Privacy in Implantable Medical Devices and Body Area Networks
Rushanan, M., Rubin, A. D., Kune, D. F., & Swanson, C. M. (2014) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp.2014.40 · Cited by 253 · see citing works
Mathematical control theory: deterministic finite dimensional systems (2nd ed.)
Sontag, E. D. (1998) · Springer eBooks · Cited by 249 · see citing works
Manufacturing and Security Challenges in 3D Printing
Zeltmann, S. E., Gupta, N., Tsoutsos, N. G., Maniatakos, M., Rajendran, J., & Karri, R. (2016) · JOM · doi:10.1007/s11837-016-1937-7 · Cited by 245 · see citing works
Observability of linear systems under adversarial attacks
Chong, M. S., Wakaiki, M., & Hespanha, J. P. (2015) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2015.7171098 · Cited by 231 · see citing works
Cui, S. R., Han, Z., Kar, S., Kim, T. T., Poor, H. V., & Tajer, A. (2012) · IEEE Signal Processing Magazine · doi:10.1109/msp.2012.2185911 · Cited by 229 · see citing works
A Decoupled Feedback Structure for Covertly Appropriating Networked Control Systems
Smith, R. S. (2011) · IFAC Proceedings Volumes · doi:10.3182/20110828-6-it-1002.01721 · Cited by 225 · see citing works
Intrusion Detection in Cyber-Physical Systems: Techniques and Challenges
Han, S., Xie, M., Chen, H., & Ling, Y. (2014) · IEEE Systems Journal · doi:10.1109/jsyst.2013.2257594 · Cited by 203 · see citing works
Cyber-physical security challenges in manufacturing systems
Wells, L. J., Camelio, J. A., Williams, C. B., & White, J. (2014) · Manufacturing Letters · doi:10.1016/j.mfglet.2014.01.005 · Cited by 193 · see citing works
Hadžiosmanović, D., Sommer, R., Zambon, E., & Hartel, P. (2014) · Annual Computer Security Applications Conference · doi:10.1145/2664243.2664277 · Cited by 190 · see citing works
Specification-Based Intrusion Detection for Advanced Metering Infrastructures
Berthier, R., & Sanders, W. H. (2011) · IEEE Pacific Rim International Symposium on Dependable Computing (PRDC) · doi:10.1109/prdc.2011.30 · Cited by 188 · see citing works
Computer Communication Within Industrial Distributed Environment—a Survey
Gaj, P., Jasperneite, J., & Felser, M. (2012) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2012.2209668 · Cited by 172 · see citing works
Cyber Security of Water SCADA Systems—Part II: Attack Detection Using Enhanced Hydrodynamic Models
Amin, S., Litrico, X., Sastry, S., & Bayen, A. M. (2012) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2012.2211874 · Cited by 156 · see citing works
Smart grid data integrity attacks: characterizations and countermeasuresπ
Giani, A., Bitar, E. Y., Garcia, M., McQueen, M., Khargonekar, P. P., & Poolla, K. R. (2011) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2011.6102324 · Cited by 148 · see citing works
Secure State Estimation Against Sensor Attacks in the Presence of Noise
Mishra, S., Shoukry, Y., Karamchandani, N., Diggavi, S. N., & Tabuada, P. (2016) · IEEE Transactions on Control of Network Systems · doi:10.1109/tcns.2016.2606880 · Cited by 146 · see citing works
Shoukry, Y., Martin, P. D., Yona, Y., Diggavi, S. N., & Srivastava, M. B. (2015) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/2810103.2813679 · Cited by 139 · see citing works
Security Tradeoffs in Cyber Physical Systems: A Case Study Survey on Implantable Medical Devices
Altawy, R., & Youssef, A. M. (2016) · IEEE Access · doi:10.1109/access.2016.2521727 · Cited by 139 · see citing works
Evaluating Electricity Theft Detectors in Smart Grid Networks
Mashima, D., & Cárdenas, Á. A. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33338-5_11 · Cited by 136 · see citing works
Emerging Security Mechanisms for Medical Cyber Physical Systems
Kocabaş, Ö., Soyata, T., & Aktaş, M. K. (2016) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2016.2520933 · Cited by 133 · see citing works
Wang, D., Wang, Z., Shen, B., Alsaadi, F. E., & Hayat, T. (2016) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2016.04.011 · Cited by 132 · see citing works
A Trusted Safety Verifier for Process Controller Code
McLaughlin, S., Zonouz, S., Pohly, D. J., & McDaniel, P. (2014) · Network and Distributed System Security Symposium · doi:10.14722/ndss.2014.23043 · Cited by 127 · see citing works
Security in stochastic control systems: Fundamental limitations and performance bounds
Bai, C.-Z., Pasqualetti, F., & Gupta, V. (2015) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2015.7170734 · Cited by 126 · see citing works
Teixeira, A. M. H., Dán, G., Sandberg, H., & Johansson, K. H. (2011) · IFAC Proceedings Volumes · doi:10.3182/20110828-6-it-1002.02210 · Cited by 122 · see citing works
Self-citationHe, H., Maple, C. R., Watson, T., Tiwari, A., Mehnen, J., Jin, Y., & Gabryś, B. (2016) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2016.7743900 · Cited by 120 · see citing works
Lin, H., Slagell, A., Martino, C. D., Kalbarczyk, Z., & Iyer, R. K. (2013) · Cyber Security and Information Intelligence Research Workshop · doi:10.1145/2459976.2459982 · Cited by 114 · see citing works
Rouf, I., Mustafa, H. A., Xu, M., Xu, W., Miller, R., & Gruteser, M. (2012) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/2382196.2382246 · Cited by 112 · see citing works
Defending against Sybil Devices in Crowdsourced Mapping Services
Wang, G., Wang, B., Wang, T., Nika, A., Zheng, H.-T., & Zhao, B. Y. (2016) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/2906388.2906420 · Cited by 108 · see citing works
A framework for the evaluation of intrusion detection systems
Cárdenas, Á. A., Baras, J. S., & Seamon, K. (2006) · Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · doi:10.1109/sp.2006.2 · Cited by 100 · see citing works
Topology Perturbation for Detecting Malicious Data Injection
Morrow, K. L., Heine, E., Rogers, K. M., Bobba, R. B., & Overbye, T. J. (2012) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2012.594 · Cited by 97 · see citing works
McLaughlin, S., & McDaniel, P. D. (2012) · Proceedings of the ACM Conference on Computer and Communications Security · doi:10.1145/2382196.2382244 · Cited by 94 · see citing works
N-Gram against the Machine: On the Feasibility of the N-Gram Network Analysis for Binary Protocols
Hadžiosmanović, D., Simionato, L., Bolzoni, D., Zambon, E., & Etalle, S. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33338-5_18 · Cited by 91 · see citing works
Power flow cyber attacks and perturbation-based defense
Davis, K., Morrow, K. L., Bobba, R. B., & Heine, E. (2012) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2012.6486007 · Cited by 89 · see citing works
Krotofil, M., Larsen, J., & Gollmann, D. (2015) · ACM Symposium on Information, Computer and Communications Security · doi:10.1145/2714576.2714599 · Cited by 89 · see citing works
Impact of integrity attacks on real-time pricing in smart grids
Tan, R., Krishna, V. B., Yau, D. K. Y., & Kalbarczyk, Z. (2013) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/2508859.2516705 · Cited by 86 · see citing works
PIPAC: Patient infusion pattern based access control scheme for wireless insulin pump system
Hei, X., Du, X., Lin, S., & Lee, I. (2013) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infcom.2013.6567115 · Cited by 83 · see citing works
Taxonomies for Reasoning About Cyber-physical Attacks in IoT-based Manufacturing Systems
Pan, Y., White, J., Schmidt, D., Elhabashy, A., Sturm, L., Camelio, J., & Williams, C. (2017) · International Journal of Interactive Multimedia and Artificial Intelligence · doi:10.9781/ijimai.2017.437 · Cited by 81 · see citing works
Characterization of a CUSUM model-based sensor attack detector
Murguia, C., & Ruths, J. (2016) · Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes · doi:10.1109/cdc.2016.7798446 · Cited by 75 · see citing works
Self-citationSRID: State Relation Based Intrusion Detection for False Data Injection Attacks in SCADA
Wang, Y., Xu, Z., Zhang, J., Xu, L., Wang, H., & Gu, G. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11212-1_23 · Cited by 74 · see citing works
Coding sensor outputs for injection attacks detection
Miao, F., Zhu, Q., Pajić, M., & Pappas, G. J. (2014) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2014.7040293 · Cited by 72 · see citing works
Impact of integrity attacks on real-time pricing in smart grids
Tan, R., Badrinath, V., David, K., Yau, K. Y., & Kalbarczyk, Z. (2013) · Cited by 72 · see citing works
On Kalman filtering in the presence of a compromised sensor: Fundamental performance bounds
Bai, C.-Z., & Gupta, V. (2014) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2014.6859155 · Cited by 65 · see citing works
Exposing Digital Forgeries in Ballistic Motion
Conotter, V., O’Brien, J. F., & Farid, H. (2011) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2011.2165843 · Cited by 65 · see citing works
Cyber attacks on AC state estimation: Unobservability and physical consequences
Liang, J., Kosut, O., & Sankar, L. (2014) · doi:10.1109/pesgm.2014.6939486 · Cited by 63 · see citing works
Attacking Fieldbus Communications in ICS: Applications to the SWaT Testbed
David, U., Jairo, G., Ole, T. N., & Alvaro, C. (2016) · Cryptology and Information Security Series · doi:10.3233/978-1-61499-617-0-75 · Cited by 63 · see citing works
A clustering-based approach to detect cyber attacks in process control systems
Kiss, I., Genge, B., & Haller, P. (2015) · 2022 IEEE 20th International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2015.7281725 · Cited by 61 · see citing works
Gerdes, R., Winstead, C., & Heaslip, K. P. (2013) · Annual Computer Security Applications Conference · doi:10.1145/2523649.2523658 · Cited by 54 · see citing works
Cumulative Attestation Kernels for Embedded Systems
LeMay, M., & Gunter, C. A. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2174811 · Cited by 51 · see citing works
Verifying Cyber-Physical Interactions in Safety-Critical Systems
Mitra, S., Wongpiromsarn, T., & Murray, R. M. (2013) · IEEE Security & Privacy · doi:10.1109/msp.2013.77 · Cited by 48 · see citing works
Hybrid Control Network Intrusion Detection Systems for Automated Power Distribution Systems
Parvania, M., Koutsandria, G., Muthukumary, V., Peisert, S., McParland, C., & Scaglione, A. (2014) · International Conference on Dependable Systems & Networks/Proceedings · doi:10.1109/dsn.2014.81 · Cited by 47 · see citing works
McLaughlin, S. (2013) · Annual Computer Security Applications Conference · doi:10.1145/2523649.2523673 · Cited by 42 · see citing works
Semantic security analysis of SCADA networks to detect malicious control commands in power grids
Lin, H., Slagell, A., Kalbarczyk, Z., Sauer, P. W., & Iyer, R. K. (2013) · doi:10.1145/2516930.2516947 · Cited by 40 · see citing works
Robust and resilient estimation for Cyber-Physical Systems under adversarial attacks
Yong, S. Z., Foo, M. Q., & Frazzoli, E. (2016) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2016.7524933 · Cited by 38 · see citing works
A hybrid network IDS for protective digital relays in the power transmission grid
Koutsandria, G., Muthukumar, V., Parvania, M., Peisert, S., McParland, C., & Scaglione, A. (2014) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2014.7007764 · Cited by 37 · see citing works
A statistical method for detecting cyber/physical attacks on SCADA systems
van Long, Fillatre, L., & Nikiforov, I. V. (2014) · The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications · doi:10.1109/cca.2014.6981373 · Cited by 37 · see citing works
Response and reconfiguration of cyber-physical control systems: A survey
Cómbita, L. F., Giraldo, J., Cárdenas, Á. A., & Quijano, N. (2015) · IEEE Colombian Conference on Automatic Control (CCAC) · doi:10.1109/ccac.2015.7345181 · Cited by 36 · see citing works
Self-citationConfiguration-based IDS for advanced metering infrastructure
Ali, M. Q., & Al-Shaer, E. S. (2013) · doi:10.1145/2508859.2516745 · Cited by 31 · see citing works
Attack Mitigation in Adversarial Platooning Using Detection-Based Sliding Mode Control
Sajjad, I., Dunn, D. D., Sharma, R., & Gerdes, R. (2015) · doi:10.1145/2808705.2808713 · Cited by 29 · see citing works
SMT-Based Observer Design for Cyber-Physical Systems under Sensor Attacks
Shoukry, Y., Chong, M. S., Wakaiki, M., Nuzzo, P., Sangiovanni-Vincentelli, A. L., Seshia, S., Hespanha, J., & Tabuada, P. (2016) · eScholarship (California Digital Library) · Cited by 26 · see citing works
A formal model for verifying stealthy attacks on state estimation in power grids
Rahman, M. A., Al-Shaer, E. S., & Rahman, M. A. (2013) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2013.6687993 · Cited by 22 · see citing works
Energy-based attack detection in networked control systems
Eyisi, E. P., & Koutsoukos, X. (2014) · doi:10.1145/2566468.2566472 · Cited by 20 · see citing works
On the security of distributed power system state estimation under targeted attacks
Vuković, O., & Dán, G. (2013) · ACM Symposium on Applied Computing · doi:10.1145/2480362.2480490 · Cited by 19 · see citing works
Using Visual Challenges to Verify the Integrity of Security Cameras
Valente, J., & Cárdenas, Á. A. (2015) · Annual Computer Security Applications Conference · doi:10.1145/2818000.2818045 · Cited by 18 · see citing works
Self-citationCyberphysical Security in Networked Control Systems [About This Issue]
How, J. P. (2015) · IEEE Control Systems · doi:10.1109/mcs.2014.2364693 · Cited by 17 · see citing works
Cyber-Physical Systems Security -- A SurveyPreprint
Humayed, A. A., Lin, J., Li, F., et al. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1701.04525 · Cited by 15 · see citing works
False data injection attacks for a class of output tracking control systems
Hou, F., Pang, Z., Zhou, Y., & Sun, D. (2015) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc.2015.7162493 · Cited by 9 · see citing works
Remote Proofs of Video Freshness for Public Spaces
Valente, J., & Cárdenas, Á. A. (2017) · Workshop on Cyber-Physical Systems Security and PrivaCy (CPS-SPC) · doi:10.1145/3140241.3140242 · Cited by 4 · see citing works
Self-citation
Flagged first, then by citations
4 of the 112 references couldn’t be matched to a known paper.
Research works printed but not linked: 12
- [16]Checkoway Stephen McCoy Damon Kantor Brian Anderson Danny Shacham Hovav Savage Stefan Koscher Karl Czeskis Alexei Roesner Franziska Kohno Tadayoshi 2011 Comprehensive Experimental Analyses of Automotive Attack Surfaces USENIX Security Symposium
- [28]Gerdes Ryan M Winstead Chris Heaslip Kevin 2013 CPS: an efficiency-motivated attack against autonomous vehicular transportation Proceedings of the Annual Computer Security Applications Conference (ACSAC) ACM 99 108
- [37]Henry Nathan Paul Nathanael McFarlane Nicole 2013 Using Bowel Sounds to Create a Forensically-aware Insulin Pump System Proceedings of Workshop on Health Information Technologies
- [43]Ishtiaq Roufa Rob Millerb Mustafaa Hossen Travis Taylora Sangho Ohb Xua Wenyuan Gruteserb Marco Trappeb Wade Seskarb Ivan 2010 Security and privacy vulnerabilities of in-car wireless networks: A tire pressure monitoring system case study Proceedings of USENIX Security Symposium 11 13
- [45]Jawurek Marek Kerschbaum Florian Danezis George 2012 SoK: Privacy technologies for smart gridsâĂŤA survey of options Microsoft Res Cambridge, UK (2012)
- [65]Ljung Lennart 1999 System Identification (2Nd Ed): Theory for the User Prentice Hall PTR Upper Saddle River, NJ, USA
- [66]Lun Yuriy Zacchia D’Innocenzo Alessandro Malavolta Ivano Di Benedetto Maria Domenica 2016 Cyber-Physical Systems Security: a Systematic Mapping Study arXiv preprint arXiv:1605.09641 (2016) · arXiv
- [69]McLaughlin Stephen 2013 CPS: Stateful Policy Enforcement for Control System Device Usage Proceedings of the Annual Computer Security Applications Conference (ACSAC) ACM New York, NY, USA 109 118
- [70]McLaughlin Stephen McDaniel Patrick 2012 SABOT: specification-based payload generation for programmable logic controllers Proceedings of conference on Computer and communications security (CCS) ACM 439 449
- [89]Rushanan Michael Rubin Aviel D Kune Denis Foo Swanson Colleen M 2014 SoK: Security and privacy in implantable medical devices and body area networks Security and Privacy (SP), 2014 IEEE Symposium on IEEE 524 539
- [90]Sajjad Imran Dunn Daniel D Sharma Rajnikant Gerdes Ryan 2015 Attack Mitigation in Adversarial Platooning Using Detection-Based Sliding Mode Control Proceedings of the ACM Workshop on Cyber-Physical Systems-Security and/or PrivaCy (CPS-SPC) (CPS-SPC ’15) ACM New York, NY, USA 43 53
- [95]Shoukry Yasser Martin Paul Yona Yair Diggavi Suhas Srivastava Mani 2015 PyCRA: Physical Challenge-Response Authentication For Active Sensors Under Spoofing Attacks Proceedings of the Conference on Computer and Communications Security (CCS) (CCS’15) ACM New York, NY, USA 1004 1015
Cited by
Sorted by citations
Deep Learning for Generic Object Detection: A Survey
Liu, L., Ouyang, W., Wang, X., Fieguth, P., Chen, J., Liu, X., & Pietikäinen, M. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-019-01247-4 · Cited by 2,965 · see citing works
A Survey of Cyber Attacks on Cyber Physical Systems: Recent Advances and Challenges
Duo, W., Zhou, M., & Abusorrah, A. M. (2022) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2022.105548 · Cited by 599 · see citing works
Fake news detection: A hybrid CNN-RNN based deep learning approach
Nasir, J. A., Khan, O. S., & Varlamis, I. (2021) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2020.100007 · Cited by 568 · see citing works
A systems and control perspective of CPS security
Dibaji, S. M., Pirani, M., Flamholz, D. B., Annaswamy, A. M., Johansson, K. H., & Chakrabortty, A. (2019) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2019.04.011 · Cited by 562 · see citing works
Applications of artificial intelligence for disaster management
Sun, W., Bocchini, P., & Davison, B. D. (2020) · Natural Hazards · doi:10.1007/s11069-020-04124-3 · Cited by 491 · see citing works
Wireless Communication Technologies for Safe Cooperative Cyber Physical Systems
Balador, A., Koubâa, A., Cassioli, D., Foukalas, F. T., Severino, R., Stepanova, D., Agosta, G., Xie, J., Pomante, L., Mongelli, M., et al. (2018) · Sensors · doi:10.3390/s18114075 · Cited by 336 · see citing works
A survey on attack detection, estimation and control of industrial cyber–physical systems
Zhang, D., Wang, Q., Feng, G., Shi, Y., & Vasilakos, A. V. (2021) · ISA Transactions · doi:10.1016/j.isatra.2021.01.036 · Cited by 318 · see citing works
Secure Control of Multiagent Systems Against Malicious Attacks: A Brief Survey
He, W., Xu, W., Ge, X., Han, Q., Du, W., & Qian, F. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3126644 · Cited by 293 · see citing works
Deep learning for misinformation detection on online social networks: a survey and new perspectives
Islam, M. R., Liu, S., Wang, X., & Xu, G. (2020) · Social Network Analysis and Mining · doi:10.1007/s13278-020-00696-x · Cited by 271 · see citing works
Deep Learning-based Anomaly Detection in Cyber-physical Systems
Luo, Y., Xiao, Y., Cheng, L., Peng, G., & Yao, D. D. (2021) · ACM Computing Surveys · doi:10.1145/3453155 · Cited by 332 · see citing works
Cybersecurity of industrial cyber-physical systems: A review
Kayan, H., Nunes, M., Rana, O., Burnap, P., & Perera, C. (2022) · ACM Computing Surveys · doi:10.1145/3510410 · Cited by 261 · see citing works
Kravchik, M., & Shabtai, A. (2022) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2021.3050101 · Cited by 224 · see citing works
Detection of power grid disturbances and cyber-attacks based on machine learning
Wang, D., Wang, X., Zhang, Y., & Jin, L. (2019) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2019.02.008 · Cited by 212 · see citing works
Du, D., Zhu, M., Li, X., Fei, M., Bu, S., Wu, L., & Li, K. (2023) · Journal of Modern Power Systems and Clean Energy · doi:10.35833/mpce.2021.000604 · Cited by 190 · see citing works
A Survey on Network Security for Cyber–Physical Systems: From Threats to Resilient Design
Kim, S., Park, K., & Lu, C. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3187531 · Cited by 188 · see citing works
Deep learning-enabled anomaly detection for IoT systems
Abusitta, A., de Carvalho, G. H. S., Wahab, O. A., Halabi, T., Fung, B. C. M., & Mamoori, S. A. (2023) · Internet of Things · doi:10.1016/j.iot.2022.100656 · Cited by 184 · see citing works
Gautam, R., & Sharma, M. (2020) · Journal of Medical Systems · doi:10.1007/s10916-019-1519-7 · Cited by 177 · see citing works
Smart Grid Cyber-Physical Situational Awareness of Complex Operational Technology Attacks: A Review
Nafees, M. N., Saxena, N., Cárdenas, Á. A., Grijalva, S., & Burnap, P. (2022) · ACM Computing Surveys · doi:10.1145/3565570 · Cited by 176 · see citing works
Intrusion detection based on Machine Learning techniques in computer networks
Dina, A. S., & Manivannan, D. (2021) · Internet of Things · doi:10.1016/j.iot.2021.100462 · Cited by 187 · see citing works
Tama, B. A., & Lim, S. (2020) · Computer Science Review · doi:10.1016/j.cosrev.2020.100357 · Cited by 172 · see citing works
Umer, M., Junejo, K. N., Jilani, M. T., & Mathur, A. P. (2022) · International Journal of Critical Infrastructure Protection · doi:10.1016/j.ijcip.2022.100516 · Cited by 172 · see citing works
Optimal Stealthy Deception Attack Against Cyber-Physical Systems
Zhang, Q., Liu, K., Xia, Y., & Ma, A. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2912622 · Cited by 165 · see citing works
Digital Twins for Cyber-Physical Systems Security: State of the Art and Outlook
Eckhart, M., & Ekelhart, A. (2019) · Security and Quality in Cyber-Physical Systems Engineering · doi:10.1007/978-3-030-25312-7_14 · Cited by 158 · see citing works
Choraś, M., Demestichas, K. P., Giełczyk, A., Herrero, Á., Ksieniewicz, P., Remoundou, K., Urda, D., & Woźniak, M. (2020) · Applied Soft Computing · doi:10.1016/j.asoc.2020.107050 · Cited by 158 · see citing works
Lee, S.-W., Sidqi, H. M., Mohammadi, M., Rashidi, S., Rahmani, A. M., Masdari, M., & Hosseinzadeh, M. (2021) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2021.103111 · Cited by 144 · see citing works
Digital Twin-Based Cyber-Attack Detection Framework for Cyber-Physical Manufacturing Systems
Balta, E. C., Pease, M., Moyne, J., Barton, K., & Tilbury, D. M. (2024) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2023.3243147 · Cited by 125 · see citing works
Vahidi, S., Ghafouri, M., Au, M., Kassouf, M., Mohammadi, A., & Debbabi, M. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3251899 · Cited by 122 · see citing works
Predicting breast cancer 5-year survival using machine learning: A systematic review
Li, J., Zhou, Z., Dong, J., Fu, Y., Li, Y., Luan, Z., & Peng, X. (2021) · PLoS ONE · doi:10.1371/journal.pone.0250370 · Cited by 123 · see citing works
Ronanki, D., & Karneddi, H. (2023) · IEEE Journal of Emerging and Selected Topics in Power Electronics · doi:10.1109/jestpe.2023.3336997 · Cited by 124 · see citing works
Ye, J., Guo, L., Yang, B., Li, F., Du, L., Guan, L., & Song, W. (2020) · IEEE Journal of Emerging and Selected Topics in Power Electronics · doi:10.1109/jestpe.2020.3045667 · Cited by 117 · see citing works
A Comparative Study of Time Series Anomaly Detection Models for Industrial Control Systems
Kim, B., Alawami, M. A., Kim, E., Oh, S., Park, J., & Kim, H. (2023) · Sensors · doi:10.3390/s23031310 · Cited by 126 · see citing works
Data-Driven False Data-Injection Attack Design and Detection in Cyber-Physical Systems
Zhao, Z., Huang, Y., Zhen, Z., & Li, Y. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.2969320 · Cited by 114 · see citing works
Feng, C., & Tian, P. (2021) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3447548.3467137 · Cited by 112 · see citing works
Fake news detection: a survey of evaluation datasets
D’Ulizia, A., Caschera, M. C., Ferri, F., & Grifoni, P. (2021) · PeerJ Computer Science · doi:10.7717/peerj-cs.518 · Cited by 108 · see citing works
Deep reinforcement learning control approach to mitigating actuator attacks
Wu, C., Pan, W., Staa, R., Liu, J., Sun, G., & Wu, L. (2023) · Automatica · doi:10.1016/j.automatica.2023.110999 · Cited by 101 · see citing works
Minimizing the spread of misinformation in online social networks: A survey
Zareie, A., & Sakellariou, R. (2021) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2021.103094 · Cited by 95 · see citing works
Wang, Y., Liu, Q., Mihankhah, E., Lv, C., & Wang, D. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3077015 · Cited by 89 · see citing works
A Systematic Review on Physiological-Based Biometric Recognition Systems: Current and Future Trends
Shaheed, K., Mao, A., Qureshi, I., Kumar, M., Abbas, Q., Ullah, I., & Zhang, X. (2021) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-021-09560-3 · Cited by 90 · see citing works
Prathapchandran, K., & Janani, T. (2021) · Computer Networks · doi:10.1016/j.comnet.2021.108413 · Cited by 88 · see citing works
On the evaluation and combination of state-of-the-art features in Twitter sentiment analysis
Carvalho, J., & Plastino, A. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-020-09895-6 · Cited by 87 · see citing works
SAVIOR: Securing Autonomous Vehicles with Robust Physical Invariants.
Quinonez, R., Giraldo, J., Salazar, L., Bauman, E., Cárdenas, Á. A., & Lin, Z. (2020) · Cited by 86 · see citing works
Self-citationA review on rumour prediction and veracity assessment in online social network
Varshney, D., & Vishwakarma, D. K. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114208 · Cited by 82 · see citing works
Machine Learning for DDoS Attack Detection in Industry 4.0 CPPSs
Saghezchi, F. B., Mantas, G., Violas, M. A., de Oliveira Duarte, A. M., & Rodriguez, J. (2022) · Electronics · doi:10.3390/electronics11040602 · Cited by 81 · see citing works
Targeted Ransomware: A New Cyber Threat to Edge System of Brownfield Industrial Internet of Things
Al-Hawawreh, M. S., den Hartog, F., & Sitnikova, E. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2914390 · Cited by 81 · see citing works
Erba, A., Taormina, R., Galelli, S., Pogliani, M., Carminati, M., Zanero, S., & Tippenhauer, N. O. (2020) · Annual Computer Security Applications Conference · doi:10.1145/3427228.3427660 · Cited by 90 · see citing works
Self-citationWei, P., Wang, B., Dai, X., Li, L., & He, F. (2022) · Digital Communications and Networks · doi:10.1016/j.dcan.2022.04.021 · Cited by 75 · see citing works
Dehghani, M., Niknam, T., Ghiasi, M. I., Bayati, N., & Savaghebi, M. (2021) · Electronics · doi:10.3390/electronics10161914 · Cited by 74 · see citing works
Adaptive control of a class of strict feedback nonlinear systems under replay attacks
Huang, J., Zhao, L., & Wang, Q. (2020) · ISA Transactions · doi:10.1016/j.isatra.2020.08.001 · Cited by 72 · see citing works
Dynamic graph convolutional networks with attention mechanism for rumor detection on social media
Choi, J., Ko, T., Choi, Y., Byun, H., & Kim, C.-K. (2021) · PLoS ONE · doi:10.1371/journal.pone.0256039 · Cited by 75 · see citing works
Survey of distributed algorithms for resource allocation over multi-agent systems
Doostmohammadian, M., Aghasi, A., Pirani, M., Nekouei, E., Zarrabi, H., Keypour, R., Rikos, A. I., & Johansson, K. H. (2024) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2024.100983 · Cited by 75 · see citing works
A Systematic Review of Data Quality in CPS and IoT for Industry 4.0
Goknil, A., Nguyen, P., Sen, S., Politaki, D., Niavis, H., Pedersen, K. J., Suyuthi, A., Anand, A., & Ziegenbein, A. (2023) · ACM Computing Surveys · doi:10.1145/3593043 · Cited by 68 · see citing works
Artificial intelligence and physics-based anomaly detection in the smart grid: A survey
Gaggero, G. B., Girdinio, P., & Marchese, M. (2025) · IEEE Access · doi:10.1109/access.2025.3537410 · Cited by 67 · see citing works
Ding, S. X., Li, L., Zhao, D. Y., Louen, C. J., & Liu, T. (2022) · Automatica · doi:10.1016/j.automatica.2022.110352 · Cited by 66 · see citing works
A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems
Kim, S., & Park, K. (2021) · Applied Sciences · doi:10.3390/app11125458 · Cited by 69 · see citing works
Attack Detection in Power Distribution Systems Using a Cyber-Physical Real-Time Reference Model
Khan, M. M. S., Giraldo, J., & Parvania, M. (2021) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2021.3128034 · Cited by 66 · see citing works
Self-citationCyberattack Detection for Electric Vehicles Using Physics-Guided Machine Learning
Guo, L., Ye, J., & Yang, B. (2020) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2020.3044524 · Cited by 63 · see citing works
A Systematic Analysis of Enhancing Cyber Security Using Deep Learning for Cyber Physical Systems
Gaba, S., Budhiraja, I., Kumar, V., Martha, S., Khurmi, J., Singh, A., Singh, K. K., Askar, S. S., & Abouhawwash, M. (2024) · IEEE Access · doi:10.1109/access.2023.3349022 · Cited by 62 · see citing works
Real-Time Attack-Recovery for Cyber-Physical Systems Using Linear Approximations
Zhang, L., Chen, X., Kong, F., & Cárdenas, Á. A. (2020) · IEEE Real-Time Systems Symposium (RTSS) · doi:10.1109/rtss49844.2020.00028 · Cited by 62 · see citing works
Learning-Guided Network Fuzzing for Testing Cyber-Physical System Defences
Chen, Y., POSKITT, C. M., Sun, J., Adepu, S., & Zhang, F. (2019) · IEEE/ACM International Conference on Automated Software Engineering (ASE) · doi:10.1109/ase.2019.00093 · Cited by 62 · see citing works
An unsupervised adversarial autoencoder for cyber attack detection in power distribution grids
Zideh, M. J., Khalghani, M. R., & Solanki, S. K. (2024) · Electric Power Systems Research · doi:10.1016/j.epsr.2024.110407 · Cited by 60 · see citing works
Moriano, P., Hespeler, S. C., Li, M., & Mahbub, M. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11292-w · Cited by 73 · see citing works
A hierarchical network-oriented analysis of user participation in misinformation spread on WhatsApp
Nobre, G. P., Ferreira, C. H. G., & Almeida, J. M. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2021.102757 · Cited by 61 · see citing works
Design of Stealthy Deception Attacks With Partial System Knowledge
Zhang, Q., Liu, K., Han, D., Su, G., & Xia, Y. (2022) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2022.3146079 · Cited by 59 · see citing works
StarFL: Hybrid Federated Learning Architecture for Smart Urban Computing
Huang, A., Liu, Y., Chen, T., Zhou, Y., Sun, Q., Chai, H., & Yang, Q. (2021) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3467956 · Cited by 58 · see citing works
Torpan, S., Hansson, S., Rhinard, M., Kažemekaitytė, A., Jukarainen, P., Meyer, S. F., Schieffelers, A., Lovász, G., & Orru, K. (2021) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2021.102151 · Cited by 61 · see citing works
Secure and secret cooperation in robot swarms
Ferrer, E. C., T, T. H. M. I., Pentland, A., & Dorigo, M. (2021) · Science Robotics · doi:10.1126/scirobotics.abf1538 · Cited by 56 · see citing works
A Formal Approach to Physics-based Attacks in Cyber-physical Systems
Ruggero Lanotte, A., Merro, M., Munteanu, A., & Viganò, L. (2020) · ACM Transactions on Privacy and Security · doi:10.1145/3373270 · Cited by 54 · see citing works
Cybersecurity of Wide Area Monitoring, Protection, and Control Systems for HVDC Applications
Chen, B., Yim, S.-I., Kim, H., Kondabathini, A., & Nuqui, R. F. (2020) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2020.3022588 · Cited by 54 · see citing works
Security and Privacy in the Emerging Cyber-Physical World: A Survey
Yu, Z., Kaplan, Z., Yan, Q., & Zhang, N. (2021) · IEEE Communications Surveys and Tutorials · doi:10.1109/comst.2021.3081450 · Cited by 47 · see citing works
Characterizing Trust and Resilience in Distributed Consensus for Cyberphysical Systems
Yemini, M., Nedić, A., Goldsmith, A. J., & Gil, S. (2021) · IEEE Transactions on Robotics · doi:10.1109/tro.2021.3088054 · Cited by 53 · see citing works
Cyber-Physical Microgrids: Toward Future Resilient Communities
Vu, T., Nguyen, B. L.-H., Cheng, Z., Chow, M., & Zhang, B. (2020) · IEEE Industrial Electronics Magazine · doi:10.1109/mie.2019.2958039 · Cited by 54 · see citing works
Adversarial attacks and mitigation for anomaly detectors of cyber-physical systems
Jia, Y., Wang, J., POSKITT, C. M., Chattopadhyay, S., Sun, J., & Chen, Y. (2021) · International Journal of Critical Infrastructure Protection · doi:10.1016/j.ijcip.2021.100452 · Cited by 52 · see citing works
Deep Learning-Based Anomaly Detection in Cyber-Physical Systems: Progress and OpportunitiesPreprint
Luo, Y., Xiao, Y., Cheng, L., Peng, G., & Yao, D. D. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.13213 · Cited by 52 · see citing works
Mohammed, A. S., Reinecke, P., Burnap, P., RANA, O. F., & Anthi, E. (2022) · ACM Transactions on Cyber-Physical Systems · doi:10.1145/3548691 · Cited by 51 · see citing works
Symmetrical Simulation Scheme for Anomaly Detection in Autonomous Vehicles Based on LSTM Model
Alsulami, A. A., Al-Haija, Q. S. A., Alqahtani, A., & Alsini, R. A. I. (2022) · Symmetry · doi:10.3390/sym14071450 · Cited by 51 · see citing works
An Unsupervised Framework for Anomaly Detection in a Water Treatment System
Macas, M., & Wu, C. (2019) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2019.00212 · Cited by 51 · see citing works
Users’ ability to perceive misinformation: An information quality assessment approach
Zrnec, A., Poženel, M., & Lavbič, D. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2021.102739 · Cited by 52 · see citing works
Detection of rumor conversations in Twitter using graph convolutional networks
Lotfi, S., Mirzarezaee, M., Hosseinzadeh, M., & Seydi, V. (2021) · Applied Intelligence · doi:10.1007/s10489-020-02036-0 · Cited by 50 · see citing works
Functional observability and target state estimation in large-scale networks
Montanari, A. N., Duan, C., Aguirre, L. A., & Motter, A. E. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2113750119 · Cited by 50 · see citing works
Multimedia Social Big Data: Mining
Kumar, A., Sangwan, S. R., & Nayyar, A. (2019) · Intelligent systems reference library · doi:10.1007/978-981-13-8759-3_11 · Cited by 49 · see citing works
Semantic analysis on social networks: A survey
Bayrakdar, S., Yücedağ, İ., Şimşek, M., & Doğru, İ. A. (2020) · International Journal of Communication Systems · doi:10.1002/dac.4424 · Cited by 51 · see citing works
Zhang, J., Guo, L., & Ye, J. (2021) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2021.3121009 · Cited by 48 · see citing works
Zhao, Z., Xu, Y., Li, Y., Zhen, Z., Yang, Y., & Shi, Y. (2022) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2022.3230360 · Cited by 46 · see citing works
Reachability Analysis of Cyber-Physical Systems Under Stealthy Attacks
Zhang, Q., Liu, K., Pang, Z., Xia, Y., & Liu, T. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.3025307 · Cited by 45 · see citing works
Real-Time Adaptive Sensor Attack Detection in Autonomous Cyber-Physical Systems
Akowuah, F. E., & Kong, F. (2021) · IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS) · doi:10.1109/rtas52030.2021.00027 · Cited by 45 · see citing works
Sparse Actuator Attack Detection and Identification: A Data-Driven Approach
Zhao, Z., Xu, Y., Li, Y., Zhao, Y., Wang, B., & Wen, G. (2023) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2023.3252570 · Cited by 44 · see citing works
False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands
Dehghani, M., Ghiasi, M., Niknam, T., Kavousi‐Fard, A., & Padmanaban, S. (2020) · IEEE Access · doi:10.1109/access.2020.3027782 · Cited by 44 · see citing works
Notice of Removal: Distributed Detection and Mitigation of Biasing Attacks Over Multi-Agent Networks
Doostmohammadian, M., Zarrabi, H., Rabiee, H. R., Khan, U. A., & Charalambous, T. (2021) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2021.3115032 · Cited by 43 · see citing works
Poisoning attacks on cyber attack detectors for industrial control systems
Kravchik, M., Biggio, B., & Shabtai, A. (2021) · ACM Symposium on Applied Computing · doi:10.1145/3412841.3441892 · Cited by 43 · see citing works
A selective ensemble model for cognitive cybersecurity analysis
Jiang, Y., & Atif, Y. (2021) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2021.103210 · Cited by 42 · see citing works
Securing state reconstruction under sensor and actuator attacks: Theory and design
Showkatbakhsh, M., Shoukry, Y., Diggavi, S. N., & Tabuada, P. (2020) · Automatica · doi:10.1016/j.automatica.2020.108920 · Cited by 42 · see citing works
Jeon, Y., Kim, B., Xiong, A., Lee, D., & Han, K. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479859 · Cited by 42 · see citing works
Liu, H., Li, Y., Han, Q., & Raïssi, T. (2022) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2022.3184396 · Cited by 41 · see citing works
Real-Time Cyber Attack Localization in Distribution Systems Using Digital Twin Reference Model
Khan, M. M. S., Giraldo, J., & Parvania, M. (2023) · IEEE Transactions on Power Delivery · doi:10.1109/tpwrd.2023.3296312 · Cited by 40 · see citing works
Self-citationHussain, A., Tordera, E. M., Masip‐Bruin, X., & Leligou, H. C. (2024) · IEEE Access · doi:10.1109/access.2024.3445261 · Cited by 40 · see citing works
USMD: UnSupervised Misbehaviour Detection for Multi-Sensor Data
Alsaedi, A., Tari, Z., Mahmud, R., Moustafa, N., Mahmood, A. N., & Anwar, A. (2022) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2022.3143493 · Cited by 41 · see citing works
Fausto, A., Gaggero, G. B., Patrone, F., Girdinio, P., & Marchese, M. (2021) · Sensors · doi:10.3390/s21216970 · Cited by 42 · see citing works
Zhong, K., Yang, Z., Xiao, G., Li, X., Yang, W., & Li, K. (2021) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2021.3135412 · Cited by 39 · see citing works
Wolsing, K., Wagner, E., Saillard, A., & Henze, M. (2022) · International Symposium on Research in Attacks, Intrusions and Defenses (RAID) · doi:10.1145/3545948.3545968 · Cited by 38 · see citing works
Chen, G., Liu, Y., Yao, D., Li, H., & Ahn, C. K. (2023) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2023.3246436 · Cited by 36 · see citing works
- Authors
- Giraldo, J., Urbina, D., Cardenas, A., Valente, J., Faisal, M., Ruths, J., Tippenhauer, N. O., Sandberg, H., & Candell, R.
- Affiliations
- The University of Texas at Dallas (US)
- University of Texas at Dallas, Richardson, USA
- Singapore University of Technology and Design (SG)
- KTH Royal Institute of Technology (SE)
- National Institute of Standards and Technology (US)
- Venue
- ACM Computing Surveys
- Published
- 2018-07-25
- Volume
- 51
- Issue
- 4
- Pages
- 1-36
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- PMC
- PMC6512826
- OpenAlex
- W2803355698
- Cited by
- 535
- References
- 112
- Citations by year
- 2026: 33 · 2025: 54 · 2024: 52 · 2023: 65 · 2022: 80 · 2021: 125 · 2020: 82 · 2019: 43 · 2018: 1
- FWCI
- 38.84
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- ACM Computing Surveys (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NRF Singapore (NRF2014NCRNCR001-40)
- Swedish Research Council (2013-5523)
- NIST (70NANB16H019 and 70NANB17H282)
- NSF (CNS-1553683 and CNS-1718848)
- Swedish Civil Contingencies Agency
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Keywords
- cyber-physical systems, attack detection, industrial control systems, sensor readings, time series models, security monitoring
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
