DocumentCode
2248721
Title
Protecting Smart-Grid with Breno-Silva fast single pattern match algorithm for small patterns
Author
Pinto, Breno Silva ; Fung, Chun Che
Author_Institution
Open Inf. Security Found. (OISF), Brasilia, Brazil
Volume
6
fYear
2010
fDate
11-14 July 2010
Firstpage
3219
Lastpage
3224
Abstract
Security of future Electrical power supply and the Smart-Grid will rely on the integrity of the communication network and in particular the Internet. Intrusion Prevention System (IPS) is crucial to guard against malicious and intentional attacks. Network packet search and string processing tasks in high-speed networks are critical for secure IPS performance. Slower algorithms could mean a portion of the packets could have been bypassed and slip through the protective border, which leads to security vulnerability. A novel pattern matching algorithm is proposed in this paper and the new algorithm has worst, best, and average time complexities of O(n + 2m), O(2m), and O(n + m) respectively - when applied for large alphabets - while searching a m bytes pattern on a text of n bytes. Experiments on 256-bytes alphabet |Σ| text files have been conducted to compare the performance of the new algorithm with other alternatives. In all tests, the proposed algorithm has demonstrated an improved performance of at least 50% better on the mentioned alphabet size.
Keywords
Internet; pattern matching; power system protection; power system security; smart power grids; Breno-Silva fast single pattern match algorithm; Internet; electrical power supply; intrusion prevention system; network packet search; security vulnerability; smart-grid protection; string processing tasks; Pattern matching; Network Security; Pattern matching algorithms Intrusion Prevention systems; Smart Grid;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-6526-2
Type
conf
DOI
10.1109/ICMLC.2010.5580716
Filename
5580716
Link To Document