کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6884011 | 1444211 | 2018 | 32 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Recognizing human behaviours in online social networks
ترجمه فارسی عنوان
شناخت رفتارهای انسانی در شبکه های اجتماعی آنلاین
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
Online Social Networks (OSNs) have become a primary area of interest for cutting-edge cybersecurity applications, due to their ever increasing popularity and to the variety of data their interaction models allow for. In this perspective, most of the existing anomaly detection techniques rely on models of normal users' behaviour as defined by domain experts. However, the identification of “bad” behaviour as a probable deviation of normality still remains an open issue. Here, we propose a method for identifying human behaviour in a social network, based on a “two-step” detection strategy. In particular, we first train Markov chains on a certain number of models of normal human behaviour from social network data; then, we exploit an activity detection framework to identify unexplained activities on the basis of the normal behaviour models. Finally, the validity of our approach is tested through a set of experiments run on data extracted from Facebook.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Security - Volume 74, May 2018, Pages 355-370
Journal: Computers & Security - Volume 74, May 2018, Pages 355-370
نویسندگان
Flora Amato, Aniello Castiglione, Aniello De Santo, Vincenzo Moscato, Antonio Picariello, Fabio Persia, Giancarlo SperlÃ,