دانلود مقاله ISI انگلیسی شماره 78846
ترجمه فارسی عنوان مقاله

بهینه سازی گروه ها از تبانی حملات قوی در شبکه های ارتباطی شهری موبایل با الگوریتم های تکاملی ☆

عنوان انگلیسی
Optimizing groups of colluding strong attackers in mobile urban communication networks with evolutionary algorithms ☆
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
78846 2016 11 صفحه PDF
منبع

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

Journal : Applied Soft Computing, Volume 40, March 2016, Pages 416–426

ترجمه کلمات کلیدی
تکاملی تعاونی؛ شبکه تاخیر تحمل؛ الگوریتم های تکاملی؛ امنیت شبکه؛ مسیریابی
کلمات کلیدی انگلیسی
Cooperative co-evolution; Delay-Tolerant Network; Evolutionary algorithms; Network security; Routing
پیش نمایش مقاله
پیش نمایش مقاله  بهینه سازی گروه ها از تبانی حملات قوی در شبکه های ارتباطی شهری موبایل با الگوریتم های تکاملی ☆

چکیده انگلیسی

In novel forms of the Social Internet of Things, any mobile user within communication range may help routing messages for another user in the network. The resulting message delivery rate depends both on the users’ mobility patterns and the message load in the network. This new type of configuration, however, poses new challenges to security, amongst them, assessing the effect that a group of colluding malicious participants can have on the global message delivery rate in such a network is far from trivial. In this work, after modeling such a question as an optimization problem, we are able to find quite interesting results by coupling a network simulator with an evolutionary algorithm. The chosen algorithm is specifically designed to solve problems whose solutions can be decomposed into parts sharing the same structure. We demonstrate the effectiveness of the proposed approach on two medium-sized Delay-Tolerant Networks, realistically simulated in the urban contexts of two cities with very different route topology: Venice and San Francisco. In all experiments, our methodology produces attack patterns that greatly lower network performance with respect to previous studies on the subject, as the evolutionary core is able to exploit the specific weaknesses of each target configuration.