DMCIS 2017

DMCIS - Data Mining for Cyberphysical and Industrial Systems

A workshop organized in association with ICDM’2017
November 18, 2017 New Orleans, USA


Hotel The Roosevelt New Orleans
Room “Prytania” on the second level


8.30 - 8.35 am [Introduction by the organizers]
Scott Backhaus, Andrey Lokhov (Los Alamos National Laboratory, USA)

8.35 - 9.35 am [Keynote invited talk]
“Data Analytic Approaches to Cyber-Physical System Resiliency”
William H. Sanders (University of Illinois at Urbana-Champaign)

9.40 - 10.00 am [Accepted paper]
“Data-driven Anomaly Detection for Power System Generation Control”
Pengyuan Wang*, Manimaran Govindarasu (Iowa State University, USA)
Aditya Ashok (Pacific Northwest National Lab, USA)

10.00 - 10.15 am [Coffee break]

10.15 - 10.35 am [Invited talk]
“The Role for Data Mining in Enhancing Electric Utility Cybersecurity”
Timothy Heidel (NRECA)

10.40 - 11.00 am [Accepted paper]
“Anomaly Detection for a Water Treatment System Using Unsupervised Machine Learning”
Jun Inoue, Yoriyuki Yamagata* (National Institute of Advanced Industrial Science and Technology, Japan)
Yuqi Chen, Christopher Poskitt, Jun Sun (Singapore University of Technology and Design, Singapore)

11.00 - 11.20 am [Accepted paper]
“Pattern-Based Contextual Anomaly Detection in HVAC Systems”
Mohsin Munir*, Andreas Dengel, Sheraz Ahmed (German Research Centre for Artificial Intelligence, Germany)

11.25 - 11.45 am [Accepted paper]
“An Adaptive Modeling Framework for Bivariate Data Streams with Applications to Change Detection in Cyber-Physical Systems”
Joshua Plasse*, Jordan Noble (Imperial College London, UK)
Kary Myers (Los Alamos National Laboratory, USA)

Workshop Description and Call for papers

Modern industrial and infrastructure systems have a cyber-physical architecture, incorporating the underlying physical processes regulated by a control cyber system. In other words, they represent interdependent networks described by disparate mathematical models creating scientific challenges that go well beyond the modeling and analysis of the individual system layers. This calls for a development of novel data mining and machine learning approaches for the implementation, operation, data analytics, contol, and optimization in real-world infrastructure systems. Moreover, this complex structure is at the origin of vulnerabilities of the system to internal and external failures, as well as to the cyber attacks. Therefore, the questions of development of adequate models and methods for an efficient detection and localization of intrusions and faults, as well as proportional responses to potential attacks is of prime significance in many industrial systems, such as automotive systems, smart manufacturing, power grid, HVAC and building systems, etc.

Given that the detailed information about the underlying system topology and interactions might not be available, the emerging data mining techniques are becoming fundamental to tackle the aforementioned challenges. These techniques requires ideas and methodology from a wide variety of fields, including but not limited to statistical modeling, graph theory, nomaly detection, optimization, machine learning, time series analytics, etc. Focusing on the methodological and practical aspects of data mining for industrial systems, this workshop provides an opportunity to discuss the latest theoretical advances and real-world applications in the field of cyber-physical systems. Papers are solicited to address a wide range of topics in these areas, including but not limited to:

Data Mining Methods for Industrial Systems

Applications and Testbeds

Key dates:

Submission Instructions:

The page limit of workshop papers is 8 pages in the standard IEEE 2-column format, including the bibliography and any possible appendices. All papers must be formatted according to the IEEE Computer Society proceedings manuscript style, following IEEE ICDM 2017 submission guidelines available at:

Papers should be submitted in PDF format, electronically, using the CyberChair submission system.

Accepted papers will be included in the IEEE ICDM 2017 Workshops Proceedings volume published by IEEE Computer Society Press, and will also be included in the IEEE Xplore Digital Library. The workshop proceedings will be in a CD separated from the CD of the main conference. The CD is produced by IEEE Conference Publishing Services (CPS). Every workshop paper must have at least one paid registration in order to be published.

Keynote Speaker

Organizing Committee

Program Committee