دانلود مقاله ISI انگلیسی شماره 74050
عنوان فارسی مقاله

چارچوب تشخیص نفوذ شبکه ترکیبی و تعاونی در رایانش ابری مبتنی بر شبکه عصبی انتشار خطای بهینه سازی شده و Snort

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
74050 2016 7 صفحه PDF سفارش دهید 3200 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A Cooperative and Hybrid Network Intrusion Detection Framework in Cloud Computing Based on Snort and Optimized Back Propagation Neural Network ☆
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Procedia Computer Science, Volume 83, 2016, Pages 1200–1206

کلمات کلیدی
رایانش ابری؛ تشخیص نفوذ شبکه؛ شبکه عصبی انتشار خطا؛ Snort؛ الگوریتم بهینه سازی
پیش نمایش مقاله
پیش نمایش مقاله چارچوب تشخیص نفوذ شبکه ترکیبی و تعاونی در رایانش ابری مبتنی بر شبکه عصبی انتشار خطای بهینه سازی شده و Snort

چکیده انگلیسی

Cloud computing provides a framework for supporting end users easily attaching powerful services and applications through Internet. To give secure and reliable services in cloud computing environment is an important issue. Providing security requires more than user authentication with passwords or digital certificates and confidentiality in data transmission, because it is vulnerable and prone to network intrusions that affect confidentiality, availability and integrity of Cloud resources and offered services. To detect DoS attack and other network level malicious activities in Cloud, use of only traditional firewall is not an efficient solution. In this paper, we propose a cooperative and hybrid network intrusion detection system (CH-NIDS) to detect network attacks in the Cloud environment by monitoring network traffic, while maintaining performance and service quality. In our NIDS framework, we use Snort as a signature based detection to detect known attacks, while for detecting network anomaly, we use Back-Propagation Neural network (BPN). By applying snort prior to the BPN classifier, BPN has to detect only unknown attacks. So, detection time is reduced. To solve the problem of slow convergence of BPN and being easy to fall into local optimum, we propose to optimize the parameters of it by using an optimization algorithm in order to ensure high detection rate, high accuracy, low false positives and low false negatives with affordable computational cost. In addition, in this framework, the IDSs operate in cooperative way to oppose the DoS and DDoS attacks by sharing alerts stored in central log. In this way, unknown attacks that were detected by any IDS can easily be detected by others IDSs. This also helps to reduce computational cost for detecting intrusions at others IDS, and improve detection rate in overall the Cloud environment.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.