Abstract
As the number of internet users grows exponentially everyday, the attacks and intrusions experienced on different networks equally multiply rapidly! Most of the current Intrusion Detection Systems (IDSs) are confronted with the challenge of coping with this high volume of traffics because they have low processing throughput. The overall consequence of this short-coming is what is known as packet dropping. P system, which is otherwise called membrane system, is a maximally parallel, non-deterministic and highly distributed model inspired by the functioning of living cells in Biology. Therefore, in exploring the parallelism advantage of both membrane system and Graphics Processing Unit (GPU), the paper presents an attack detection P system implemented on GPU to minimally decrease the negative impact of packet dropping which usually emanates from busy networks. On evaluation with KDD Cup dataset, our model achieves high throughput average of about 50000p/s and classification accuracy of 95.8%.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
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Creators: | Creators Email / ID Num. Idowu, Rufai Kazeem ruffyk2001@yahoo.com Chandren M., Ravie ravie@ukm.edu.my Ali Othman, Zulaiha zao@ukm.edu.my |
Subjects: | Q Science > QA Mathematics > Computer literacy Q Science > QA Mathematics > Computers and civilization. Social aspects of computers. Hackers |
Divisions: | Universiti Teknologi MARA, Kedah > Sg Petani Campus |
Event Title: | International Conference on Computing, Mathematics and Statistics (iCMS2015) |
Event Dates: | 4-5 November 2015 |
Page Range: | pp. 1-10 |
Keywords: | Membrane computing, intrusion detection, network security, GPU |
Date: | 2015 |
URI: | https://ir.uitm.edu.my/id/eprint/53757 |