کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10340800 | 695264 | 2005 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multiple behavior information fusion based quantitative threat evaluation
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
How to evaluate network security threat quantitatively is one of key issues in the field of network security, which is vital for administrators to make decision on the security of computer networks. A novel model of security threat evaluation with a series of quantitative indices is proposed on the analysis of prevalent network intrusions. This model is based on multiple behavior information fusion and two indices of privilege validity and service availability that are proposed to evaluate the impact of prevalent network intrusions on system security, so as to provide security evolution over time, i.e., monitor security changes with respect to modification of security factors. The Markov model and the algorithm of D-S evidence reasoning are proposed to measure these two indices, respectively. Compared with other methods, this method mitigates the impact of unsuccessful intrusions on threat evaluation. It evaluates the impact of important intrusions on system security comprehensively and helps administrators to insight into intrusion steps, determine security state and identify dangerous intrusion traces. Testing in a real network environment shows that this method is reasonable and feasible in alleviating the tremendous task of data analysis and facilitating the understanding of the security evolution of the system for its administrators.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Security - Volume 24, Issue 3, May 2005, Pages 218-231
Journal: Computers & Security - Volume 24, Issue 3, May 2005, Pages 218-231
نویسندگان
Xiu-Zhen Chen, Qing-Hua Zheng, Xiao-Hong Guan, Chen-Guang Lin, Jie Sun,