Title
illiad: InteLLigent Invariant and Anomaly Detection in Cyber-Physical Systems.
Abstract
Cyber-physical systems (CPSs) are today ubiquitous in urban environments. Such systems now serve as the backbone to numerous critical infrastructure applications, from smart grids to IoT installations. Scalable and seamless operation of such CPSs requires sophisticated tools for monitoring the time series progression of the system, dynamically tracking relationships, and issuing alerts about anomalies to operators. We present an online monitoring system (illiad) that models the state of the CPS as a function of its relationships between constituent components, using a combination of model-based and data-driven strategies. In addition to accurate inference for state estimation and anomaly tracking, illiad also exploits the underlying network structure of the CPS (wired or wireless) for state estimation purposes. We demonstrate the application of illiad to two diverse settings: a wireless sensor motes application and an IEEE 33-bus microgrid.
Year
DOI
Venue
2018
10.1145/3066167
ACM TIST
Keywords
Field
DocType
IoT, Urban computing, big-data, state-estimation, urban informatics
Anomaly detection,Data mining,Wireless,Smart grid,Computer science,Critical infrastructure,Cyber-physical system,Urban computing,Microgrid,Scalability,Distributed computing
Journal
Volume
Issue
ISSN
9
3
2157-6904
Citations 
PageRank 
References 
1
0.35
14
Authors
7
Name
Order
Citations
PageRank
Nikhil Muralidhar121.38
Chen Wang214146.56
Nathan Self31019.65
Marjan Momtazpour4142.45
Kiyoshi Nakayama5277.51
Ratnesh Sharma69811.61
Naren Ramakrishnan71913176.25