Detecting Sensors and Inferring their Relations at Level-0 in Industrial Cyber-Physical Systems

Kalyan Perumalla; Srikanth Yoginath; Juan Lopez

doi:10.1109/HST47167.2019.9032891

Detecting Sensors and Inferring their Relations at Level-0 in Industrial Cyber-Physical Systems

Kalyan Perumalla, Srikanth Yoginath, Juan Lopez

Systems and Decision Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

While there exist tools and techniques to discover, identify, map, and analyze cyber physical components at higher levels of the cyber space, there is a lack of capabilities to reach down to the sensors at the bottom-most levels, such as levels 0 and 1 of the Purdue Enterprise Reference Model for cyber-physical systems (CPS). Conventional information technology (IT)-based tools reach as far as the network-side of programmable logic controllers, but are inadequate to access and analyze the physical side of the CPS infrastructure that directly interfaces with the actual physical processes and systems. In this paper, we present our research and development efforts aimed at addressing this gap, by building a system called Deep-cyberia (Deep Cyber-Physical System Interrogation and Analysis) that incorporates algorithms and interfaces aimed at uncovering sensors and computing estimates of correlations among them.

Original language	English
Title of host publication	2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728150925
DOIs	https://doi.org/10.1109/HST47167.2019.9032891
State	Published - Nov 2019
Event	2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019 - Woburn, United States Duration: Nov 5 2019 → Nov 6 2019

Publication series

Name	2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019

Conference

Conference	2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019
Country/Territory	United States
City	Woburn
Period	11/5/19 → 11/6/19

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

causality
correlations
deep learning
inference
machine learning
programmable logic controllers
sensors

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/HST47167.2019.9032891

Cite this

Perumalla, K., Yoginath, S., & Lopez, J. (2019). Detecting Sensors and Inferring their Relations at Level-0 in Industrial Cyber-Physical Systems. In 2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019 Article 9032891 (2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HST47167.2019.9032891

Perumalla, Kalyan ; Yoginath, Srikanth ; Lopez, Juan. / Detecting Sensors and Inferring their Relations at Level-0 in Industrial Cyber-Physical Systems. 2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019).

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Perumalla, K, Yoginath, S & Lopez, J 2019, Detecting Sensors and Inferring their Relations at Level-0 in Industrial Cyber-Physical Systems. in 2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019., 9032891, 2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019, Woburn, United States, 11/5/19. https://doi.org/10.1109/HST47167.2019.9032891

Detecting Sensors and Inferring their Relations at Level-0 in Industrial Cyber-Physical Systems. / Perumalla, Kalyan; Yoginath, Srikanth; Lopez, Juan.
2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 9032891 (2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Perumalla K, Yoginath S, Lopez J. Detecting Sensors and Inferring their Relations at Level-0 in Industrial Cyber-Physical Systems. In 2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 9032891. (2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019). doi: 10.1109/HST47167.2019.9032891

Detecting Sensors and Inferring their Relations at Level-0 in Industrial Cyber-Physical Systems

Abstract

Publication series

Conference

Funding

Keywords

UN SDGs

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