Large in-memory cyber-physical security-related analytics via scalable coherent shared memory architectures

Williams, John R., Herrero, Sergio, Leonardi, Christopher, Chan, Stephen, Sanchez, Abel and Aung, Zeyar (2011). Large in-memory cyber-physical security-related analytics via scalable coherent shared memory architectures. In: 2011 IEEE Symposium on Computational Intelligence in Cyber Security (CICS 2011) Proceedings. IEEE Symposium on Computational Intelligence in Cyber Security (CISC2011), Paris, France, (1-9). 11-15 April 2011. doi:10.1109/CICYBS.2011.5949414


Author Williams, John R.
Herrero, Sergio
Leonardi, Christopher
Chan, Stephen
Sanchez, Abel
Aung, Zeyar
Title of paper Large in-memory cyber-physical security-related analytics via scalable coherent shared memory architectures
Conference name IEEE Symposium on Computational Intelligence in Cyber Security (CISC2011)
Conference location Paris, France
Conference dates 11-15 April 2011
Proceedings title 2011 IEEE Symposium on Computational Intelligence in Cyber Security (CICS 2011) Proceedings
Journal name IEEE SSCI 2011: Symposium Series on Computational Intelligence - CICS 2011: 2011 IEEE Symposium on Computational Intelligence in Cyber Security
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2011
Sub-type Fully published paper
DOI 10.1109/CICYBS.2011.5949414
Open Access Status Not Open Access
ISBN 9781424499052
Start page 1
End page 9
Total pages 9
Language eng
Abstract/Summary Cyber-physical security-related queries and analytics run on traditional relational databases can take many hours to return. Furthermore, programming analytics on distributed databases requires great skill, and there is a shortage of such talent worldwide. In this talk on computational intelligence within cyber security, we will review developments of processing large datasets in-memory using a coherent shared memory approach. The coherent shared memory approach allows programmers to view a cluster of servers as a system with a single large RAM. By hiding the actual system architecture under a software layer, we proffer a more intuitive programming model. Furthermore, the design of applications is “timeless” since hardware upgrades require no changes to the software. The advantages of shared memory are countered by some disadvantages in that race conditions can occur; however, in many of these cases, we can provide models that protect us against such problems. Exemplars include sensemaking of Twitter feeds, the processing of Smart Meter datasets, and the large scale simulation of the caching of files at disparate points around the globe.
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Conference Paper
Collection: School of Mechanical & Mining Engineering Publications
 
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Created: Thu, 17 Mar 2016, 15:42:33 EST by Christopher Leonardi on behalf of School of Mechanical and Mining Engineering