Open AccessOptimizing SIEM Throughput on the Cloud Using Parallelization
Author(s) -
Mansaf Alam,
Asif Ihsan,
Muazzam A. Khan,
Qaisar Javaid,
Abid Hossain Khan,
Jawad Manzoor,
Adnan Akhundzada,
Muhammad Khurram Khan,
Sajid Farooq
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0162746
Subject(s) - computer science , cloud computing , throughput , process (computing) , event (particle physics) , response time , service (business) , parallel computing , distributed computing , operating system , physics , economy , quantum mechanics , economics , wireless
Processing large amounts of data in real time for identifying security issues pose several performance challenges, especially when hardware infrastructure is limited. Managed Security Service Providers (MSSP), mostly hosting their applications on the Cloud, receive events at a very high rate that varies from a few hundred to a couple of thousand events per second (EPS). It is critical to process this data efficiently, so that attacks could be identified quickly and necessary response could be initiated. This paper evaluates the performance of a security framework OSTROM built on the Esper complex event processing (CEP) engine under a parallel and non-parallel computational framework. We explain three architectures under which Esper can be used to process events. We investigated the effect on throughput, memory and CPU usage in each configuration setting. The results indicate that the performance of the engine is limited by the number of events coming in rather than the queries being processed. The architecture where 1/4th of the total events are submitted to each instance and all the queries are processed by all the units shows best results in terms of throughput, memory and CPU usage.