Applying Catastrophe Theory for Network Anomaly Detection in Cloud Computing Traffic
المؤلفون المشاركون
Khatibzadeh, Leila
Bornaee, Zarrintaj
Ghaemi Bafghi, Abbas
المصدر
Security and Communication Networks
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-05-02
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
In spite of the tangible advantages of cloud computing, it is still vulnerable to potential attacks and threats.
In light of this, security has turned into one of the main concerns in the adoption of cloud computing.
Therefore, an anomaly detection method plays an important role in providing a high protection level for network security.
One of the challenges in anomaly detection, which has not been seriously considered in the literature, is applying the dynamic nature of cloud traffic in its prediction while maintaining an acceptable level of accuracy besides reducing the computational cost.
On the other hand, to overcome the issue of additional training time, introducing a high-speed algorithm is essential.
In this paper, a network traffic anomaly detection model grounded in Catastrophe Theory is proposed.
This theory is effective in depicting sudden change processes of the network due to the dynamic nature of the cloud.
Exponential Moving Average (EMA) is applied for the state variable in sliding window to better show the dynamicity of cloud network traffic.
Entropy is used as one of the control variables in catastrophe theory to analyze the distribution of traffic features.
Our work is compared with Wei Xiong et al.’s Catastrophe Theory and achieved a maximum improvement in the percentage of Detection Rate in week 4 Wednesday (7.83%) and a 0.31% reduction in False Positive Rate in week 5 Monday.
Additional accuracy parameters are checked and the impact of sliding window size in sensitivity and specificity is considered.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Khatibzadeh, Leila& Bornaee, Zarrintaj& Ghaemi Bafghi, Abbas. 2019. Applying Catastrophe Theory for Network Anomaly Detection in Cloud Computing Traffic. Security and Communication Networks،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1210473
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Khatibzadeh, Leila…[et al.]. Applying Catastrophe Theory for Network Anomaly Detection in Cloud Computing Traffic. Security and Communication Networks No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1210473
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Khatibzadeh, Leila& Bornaee, Zarrintaj& Ghaemi Bafghi, Abbas. Applying Catastrophe Theory for Network Anomaly Detection in Cloud Computing Traffic. Security and Communication Networks. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1210473
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1210473
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