Using Of Neuro-Fuzzy Classifier for Intrusion Detection Systems

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Nataj Solhdar Mohammad Hassan

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: C4I JOURNAL Year:2021 | Volume:5 | Issue:2 Page(s): 46-61

Download Full-Text

Persian Verion

View:

223

Download:

Cites:

Information Journal Paper

Title

Using Of Neuro-Fuzzy Classifier for Intrusion Detection Systems

Author(s)

Nataj Solhdar Mohammad Hassan | Issue Writer Certificate

Keywords

Intrusion Detection System

neural network

neuro-fuzzy classifier

ANFIS

NSLKDD

Abstract

One of the tools of artificial intelligence is the adaptive neural-fuzzy inference system (ANFIS), which is used in this article to build an Intrusion Detection System and we call it the neural-fuzzy classifier. The Intrusion Detection System based on ANFIS is an anomaly based Intrusion Detection System that uses fuzzy logic and neural network to detect if malicious activity is taking place on a network. This paper describes the architecture of the ANFIS and its components. The sample fuzzy rules are developed for some kinds of attacks and the testing results with actual network data are described. Our experiments and evaluations were performed with the NSLKDD intrusion detection dataset which is a version of the KDD Cup99 intrusion detection evaluation dataset prepared and managed by MIT Lincoln Laboratories. Finally, this paper tries to show the efficiency of the designed model by examining the performance of the "neural-fuzzy adaptive inference system" model on a standard and comprehensive set.

Cites

No record.

References

No record.

Cite

APA: Copy

Nataj Solhdar, Mohammad Hassan. (2021). Using Of Neuro-Fuzzy Classifier for Intrusion Detection Systems. C4I JOURNAL, 5(2 ), 46-61. SID. https://sid.ir/paper/954986/en

Vancouver: Copy

Nataj Solhdar Mohammad Hassan. Using Of Neuro-Fuzzy Classifier for Intrusion Detection Systems. C4I JOURNAL[Internet]. 2021;5(2 ):46-61. Available from: https://sid.ir/paper/954986/en

IEEE: Copy

Mohammad Hassan Nataj Solhdar, “Using Of Neuro-Fuzzy Classifier for Intrusion Detection Systems,” C4I JOURNAL, vol. 5, no. 2 , pp. 46–61, 2021, [Online]. Available: https://sid.ir/paper/954986/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops