TY - GEN
T1 - Utilizing semantic big data for realizing a national-scale infrastructure vulnerability analysis system
AU - Lee, Sangkeun
AU - Chinthavali, Supriya
AU - Duan, Sisi
AU - Shankar, Mallikarjun
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/6/26
Y1 - 2016/6/26
N2 - Critical Infrastructure systems (CIs) such as energy, water, transportation, and communication are highly interconnected and mutually dependent in complex ways. Robust modeling of CIs' interconnections is crucial to identify vulnerabilities in the CIs. We present a vision of national-scale Infrastructure Vulnerability Analysis System (IVAS) leveraging Semantic Big Data (SBD) tools, Big Data, and Geographical Information Systems (GIS) tools. We first survey existing approaches on vulnerability analysis of critical infrastructures and discuss relevant systems and tools aligned with our vision. Next, we present a generic system architecture and discuss challenges including: (1) Constructing and managing a CI network-of-networks graph, (2) Performing analytic operations at scale, and (3) Interactive visualization of analytic output to generate meaningful insights. We argue that this architecture acts as a baseline to realize a national-scale network based vulnerability analysis system.
AB - Critical Infrastructure systems (CIs) such as energy, water, transportation, and communication are highly interconnected and mutually dependent in complex ways. Robust modeling of CIs' interconnections is crucial to identify vulnerabilities in the CIs. We present a vision of national-scale Infrastructure Vulnerability Analysis System (IVAS) leveraging Semantic Big Data (SBD) tools, Big Data, and Geographical Information Systems (GIS) tools. We first survey existing approaches on vulnerability analysis of critical infrastructures and discuss relevant systems and tools aligned with our vision. Next, we present a generic system architecture and discuss challenges including: (1) Constructing and managing a CI network-of-networks graph, (2) Performing analytic operations at scale, and (3) Interactive visualization of analytic output to generate meaningful insights. We argue that this architecture acts as a baseline to realize a national-scale network based vulnerability analysis system.
KW - Big data
KW - Critical infrastructure network
KW - Graph analysis
KW - Interdependency
KW - Large-scale
KW - Vulnerability analysis
UR - https://www.scopus.com/pages/publications/85053695764
U2 - 10.1145/2928294.2928295
DO - 10.1145/2928294.2928295
M3 - Conference contribution
AN - SCOPUS:85053695764
SN - 9781450342995
T3 - Proceedings of the ACM SIGMOD International Conference on Management of Data
BT - Proceedings of the International Workshop on Semantic Big Data, SBD 2016, in conjunction with the 2016 ACM SIGMOD/PODS Conference
A2 - Gruenwald, Le
A2 - Groppe, Sven
PB - Association for Computing Machinery
T2 - 2016 International Workshop on Semantic Big Data, SBD 2016, in conjunction with the 2016 ACM SIGMOD/PODS Conference
Y2 - 1 July 2016
ER -