An intelligent CRF based feature selection for effective intrusion detection
المؤلفون المشاركون
Vijayakumar, Pandi
Kannan, Arputharaj
Ganapathy, Sannasi
Yogesh, Palanichamy
المصدر
The International Arab Journal of Information Technology
العدد
المجلد 13، العدد 1 (31 يناير/كانون الثاني 2016)8ص.
الناشر
تاريخ النشر
2016-01-31
دولة النشر
الأردن
عدد الصفحات
8
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الموضوعات
الملخص EN
As the Internet applications are growing rapidly, the intrusions to the networking system are also becoming high.
Insuch a scenario, it is necessary to provide security to the networks by means of effective intrusion detection and prevention methods.
This can be achieved mainly by developing efficient intrusion detecting systems that use efficient algorithms which can identify the abnormal activities in the network traffic and protect the network resources from illegal penetrations by intruders.
Though many intrusion detection systems have been proposed in the past, the existing network intrusion detections have limitations in terms of detection time and accuracy.
To overcome these drawbacks, we propose a new intrusion detection system in this paper by developing a new intelligent Conditional Random Field (CRF) based feature selection algorithm to optimize the number of features.
In addition, an existing layered approach based algorithm is used to perform classification with these reduced features.
This intrusion detection system provides high accuracy and achieves efficiency in attack detection compared to the existing approaches.
The major advantages of this proposed system are reduction in detection time, increase in classification accuracy and reduction in false alarm rates.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ganapathy, Sannasi& Vijayakumar, Pandi& Yogesh, Palanichamy& Kannan, Arputharaj. 2016. An intelligent CRF based feature selection for effective intrusion detection. The International Arab Journal of Information Technology،Vol. 13, no. 1.
https://search.emarefa.net/detail/BIM-581138
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ganapathy, Sannasi…[et al.]. An intelligent CRF based feature selection for effective intrusion detection. The International Arab Journal of Information Technology Vol. 13, no. 1 (Jan. 2016).
https://search.emarefa.net/detail/BIM-581138
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ganapathy, Sannasi& Vijayakumar, Pandi& Yogesh, Palanichamy& Kannan, Arputharaj. An intelligent CRF based feature selection for effective intrusion detection. The International Arab Journal of Information Technology. 2016. Vol. 13, no. 1.
https://search.emarefa.net/detail/BIM-581138
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-581138
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر