Parallel Scalable Approximate Matching Algorithm
for Network Intrusion Detection Systems
Adnan Hnaif1,
Khalid Jaber1, Mohammad Alia1, and Mohammed Daghbosheh2
1Faculty of
Science and Information Technology, Al Zaytoonah University of Jordan, Jordan
2Faculty of
Science and Information Technology, Irbid National University of Jordan, Jordan
Abstract: Matching algorithms are working to find the exact or
the approximate matching between text “T” and pattern “P”, due to the
development of a computer processor, which currently contains a set of
multi-cores, multitasks can be performed simultaneously. This technology makes
these algorithms work in parallel to improve their speed matching performance.
Several exact string matching and approximate matching algorithms have been
developed to work in parallel to find the correspondence between text “T” and
pattern “P”. This paper proposed two models: First, parallelized the Direct
Matching Algorithm (PDMA) in multi-cores architecture using OpenMP technology.
Second, the PDMA implemented in Network Intrusion Detection Systems (NIDS) to
enhance the speed of the NIDS detection engine. The PDMA can be achieved more
than 19.7% in parallel processing time compared with sequential matching
processing. In addition, the performance of the NIDS detection engine improved
for more than 8% compared to the current SNORT-NIDS detection engine.
Keywords: Exact matching algorithms, approximate matching algorithms, parallel
processing, network intrusion detection systems.
Received
February 13, 2020; accepted June 17, 2020