دانلود مقاله ISI انگلیسی شماره 76957
عنوان فارسی مقاله

به سوی یک سیستم تشخیص ناهنجاری بدون نظارت عملی تر

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
76957 2013 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Toward a more practical unsupervised anomaly detection system
منبع

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

Journal : Information Sciences, Volume 231, 10 May 2013, Pages 4–14

کلمات کلیدی
سیستم تشخیص نفوذ؛ خوشه بندی؛ SVM-یک کلاس؛ تشخیص ناهنجاری
پیش نمایش مقاله
پیش نمایش مقاله به سوی یک سیستم تشخیص ناهنجاری بدون نظارت عملی تر

چکیده انگلیسی

During the last decade, various machine learning and data mining techniques have been applied to Intrusion Detection Systems (IDSs) which have played an important role in defending critical computer systems and networks from cyber attacks. Unsupervised anomaly detection techniques have received a particularly great amount of attention because they enable construction of intrusion detection models without using labeled training data (i.e., with instances preclassified as being or not being an attack) in an automated manner and offer intrinsic ability to detect unknown attacks; i.e., 0-day attacks. Despite the advantages, it is still not easy to deploy them into a real network environment because they require several parameters during their building process, and thus IDS operators and managers suffer from tuning and optimizing the required parameters based on changes of their network characteristics. In this paper, we propose a new anomaly detection method by which we can automatically tune and optimize the values of parameters without predefining them. We evaluated the proposed method over real traffic data obtained from Kyoto University honeypots. The experimental results show that the performance of the proposed method is superior to that of the previous one.

خرید مقاله
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