DocumentCode :
1797718
Title :
Proposed anticipating learning classifier system for cloud intrusion detection (ALCS-CID)
Author :
Alsharafat, Wafa Slaibi
Author_Institution :
Prince Hussein Bin Abdullah Fac. of Inf. Technol., Al al-Bayt Univ., Mafraq, Jordan
fYear :
2014
fDate :
15-17 Nov. 2014
Firstpage :
315
Lastpage :
318
Abstract :
Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This Model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD´99.
Keywords :
authorisation; cloud computing; computer network security; data privacy; ALCS-CID; cloud computing; cloud intrusion detection system; cloud resources; learning classifier system; network environment; network users; online systems; privacy contravention; security mechanism; unauthorized resource access; Cloud computing; Conferences; Detectors; Genetic algorithms; Hidden Markov models; Intrusion detection; Training; Anticipating classifier system; Cloud computing; IDS;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Informatics (ICSAI), 2014 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-5457-5
Type :
conf
DOI :
10.1109/ICSAI.2014.7009306
Filename :
7009306
Link To Document :
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