دانلود مقاله ISI انگلیسی شماره 76947
عنوان فارسی مقاله

تشخیص ناهنجاری شبکه از طریق تجزیه و تحلیل غیر خطی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
76947 2010 19 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Network anomaly detection through nonlinear analysis
منبع

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

Journal : Computers & Security, Volume 29, Issue 7, October 2010, Pages 737–755

کلمات کلیدی
تشخیص ناهنجاری؛ تجزیه و تحلیل تعیین مقدار باز گشت؛ تجزیه و تحلیل غیر خطی؛ Non-stationarity؛ ماشین آلات پشتیبانی بردار
پیش نمایش مقاله
پیش نمایش مقاله تشخیص ناهنجاری شبکه از طریق تجزیه و تحلیل غیر خطی

چکیده انگلیسی

Nowadays every network is susceptible on a daily basis to a significant number of different threats and attacks both from the inside and outside world. Some attacks only exploit system vulnerabilities and their traffic pattern is undistinguishable from normal behavior, but in many cases the attack mechanisms combine protocol or OS tampering activity with a specific traffic pattern having its own particular characteristics. Since these traffic anomalies are now conceived as a structural part of the overall network traffic, it is more and more important to automatically detect, classify and identify them in order to react promptly and adequately. In this work we present a novel approach to network-based anomaly detection based on the analysis of non-stationary properties and “hidden” recurrence patterns occurring in the aggregated IP traffic flows. In the observation of the above transition patterns for detecting anomalous behaviors, we adopted recurrence quantification analysis, a nonlinear technique widely used in many science fields to explore the hidden dynamics and time correlations of statistical time series. Our model demonstrated to be effective for providing a deterministic interpretation of recurrence patterns originated by the complex traffic dynamics observable during the occurrence of “noisy” network anomaly phenomena (characterized by measurable variations in the statistical properties of the traffic time series), and hence for developing qualitative and quantitative observations that can be reliably used in detecting such events.

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