Multithreaded Scalable Matching Algorithm For Intrusion Detection Systems

Simple item page
dc.contributor.authorHnaif, Adnan Ahmad Abdelfattah
dc.date.accessioned2018-10-25T02:05:01Z
dc.date.available2018-10-25T02:05:01Z
dc.date.issued2010-05
dc.description.abstractThe increasing speed of today’s computer networks directly affects the performance of Network Intrusion Detection Systems (NIDS) in terms of speed of detection of threats. Therefore, the performance of the existing algorithms needs to be improved both in sequential and parallel to enhance the speed of the detection engine used in SNORT-NIDS. Hence, this thesis defines a new algorithm called the Distributed Packet Header Matching algorithm (DPHM), and a New Network Intrusion Detection Systems (NNIDS) platform using hybrid technology in order to increase the overall performance of SNORT-NIDS. The DPHM algorithm converts the header rule sets into weights and stores them in a lookup table. It then matches the incoming packets header with the headers rule sets. The speed of the SNORT-NIDS matching process is enhanced using the proposed learning process which is contained within the DPHM algorithm. Furthermore, the NNIDS platform will distribute the incoming packets payload into two scenarios: In the first scenario, the incoming packets payload will distribute among available processor in shared memory architecture using Message Passing Interface (MPI) library. In the second scenario, the incoming packets payloads will be distributed amongst available processors with multiple-cores processors using a hybrid of MPI library and OpenMP library in shared memory architecture.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/6881
dc.language.isoenen_US
dc.publisherUniversiti Sains Malaysiaen_US
dc.subjectMultithreaded scalable matching algorithmen_US
dc.subjectfor intrusion detection systemsen_US
dc.titleMultithreaded Scalable Matching Algorithm For Intrusion Detection Systemsen_US
dc.typeThesisen_US
Files
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Pusat IPv6 Termaju Negara - Tesis