ناشر تخصصی کنفرانس های ایران

لطفا کمی صبر نمایید

Publisher of Iranian Journals and Conference Proceedings

Please waite ..
Publisher of Iranian Journals and Conference Proceedings
Login |Register |Help |عضویت کتابخانه ها
Paper
Title

Join of Fuzzy Genetic approaches for Intrusion Detection An Efficient Intrusion Detection System Based on Fuzzy Genetic approaches

Year: 1392
COI: TIAU01_810
Language: EnglishView: 517
متن کامل این Paper منتشر نشده است و فقط به صورت چکیده یا چکیده مبسوط در پایگاه موجود می باشد.
توضیح: معمولا کلیه مقالاتی که کمتر از ۵ صفحه باشند در پایگاه سیویلیکا اصل Paper (فول تکست) محسوب نمی شوند و فقط کاربران عضو بدون کسر اعتبار می توانند فایل آنها را دریافت نمایند.

Buy and Download

متن کامل (فول تکست) این مقاله منتشر نشده و یا در سایت موجود نیست و امکان خرید آن فراهم نمی باشد.

Authors

s.o Azarkasb - Faculty of Computer Engineering, Qazvin Branch Azad University, Tehran, Iran.

Abstract:

One of the solutions for the security of the systems and computer networks is the formation of intrusion detection systems. In the design of these systems, the techniques of artificial intelligence such as neural network, data miningtechniques, expert systems, genetic algorithms and fuzzy systems are applied. The main aim is the design of thesystem that besides exact detection is with low error. The main aim of detection in these systems is their analyzer. Itseems that if the input of analyzer of the systems is language variables and final detection is done as fuzzy inference,the results of the analysis get better and an exact detection is done. In addition to reduction of error, it can present good information in the form of fuzzy rules to the security expert of the system. Genetic algorithms by flexible and prevalent searching ability can be applied for optimized learning of fuzzy system rule base. The current paper aimed to evaluate, design and implement fuzzy genetic intrusion detection system. The experiments and the results showed the considerable effect of using the proposed architecture on the improvement of detection. [Life Science Journal 2013;X(X): X-XX]. (ISSN: 1545-0740).

Keywords:

Paper COI Code

This Paper COI Code is TIAU01_810. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/291303/

How to Cite to This Paper:

If you want to refer to this Paper in your research work, you can simply use the following phrase in the resources section:
Azarkasb, s.o,1392,Join of Fuzzy Genetic approaches for Intrusion Detection An Efficient Intrusion Detection System Based on Fuzzy Genetic approaches,National Conference on Applied Research in Science and Engineering,Takestan,https://civilica.com/doc/291303

Research Info Management

Certificate | Report | من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:

اطلاعات استنادی این Paper را به نرم افزارهای مدیریت اطلاعات علمی و استنادی ارسال نمایید و در تحقیقات خود از آن استفاده نمایید.

Scientometrics

The specifications of the publisher center of this Paper are as follows:
Type of center: Azad University
Paper count: 10,297
In the scientometrics section of CIVILICA, you can see the scientific ranking of the Iranian academic and research centers based on the statistics of indexed articles.

Share this page

More information about COI

COI stands for "CIVILICA Object Identifier". COI is the unique code assigned to articles of Iranian conferences and journals when indexing on the CIVILICA citation database.

The COI is the national code of documents indexed in CIVILICA and is a unique and permanent code. it can always be cited and tracked and assumed as registration confirmation ID.

Support