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مدل محاسباتی جهت ارزیابی عملکرد عامل عملیات نفوذ در شبکه‌های اجتماعی برخط | ||
| پدافند الکترونیکی و سایبری | ||
| مقاله 8، دوره 12، شماره 1 - شماره پیاپی 45، خرداد 1403، صفحه 89-107 اصل مقاله (1.06 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| نویسندگان | ||
| غلامرضا بازدار1؛ محمد عبداللهی ازگمی* 2 | ||
| 1دانشجوی دکتری، دانشگاه امام حسین (ع)، تهران، ایران | ||
| 2استاد، دانشگاه علم و صنعت، تهران، ایران | ||
| تاریخ دریافت: 11 بهمن 1402، تاریخ بازنگری: 31 فروردین 1403، تاریخ پذیرش: 14 اردیبهشت 1403 | ||
| چکیده | ||
| گسترش شتابان استفاده از شبکه‌های اجتماعی برخط در میان جامعه، زمینه مستعدی برای اجرای عملیات‌های نفوذ شناختی و اجتماعی را فراهم آورده است. طرح‌ریزی و اجرای بهینه عملیات نفوذ، وابسته به داشتن یک چارچوب مناسب جهت ارزیابی این عملیات است. ارزیابی عامل‌ها و بازیگران مؤثر در عملیات نفوذ از ملزومات اصلی ارزیابی عملیات نفوذ است. با توجه به پویایی شبکه‌های اجتماعی برخط و تولید روزافزون داده‌های انبوه در آن، استفاده از رویکرد محاسباتی جهت ارزیابی عملیات نفوذ ضروری است. لذا هدف این تحقیق، یافتن مدلی محاسباتی جهت ارزیابی عامل‌های عملیات نفوذ در شبکه‌های اجتماعی برخط است. به‌طورکلی روش‌های ارزیابی نفوذ عامل را می‌توان به سه دسته کلی ارزیابی کیفی، ارزیابی کمی و ارزیابی محاسباتی تقسیم کرد. روش‌های ارزیابی محاسباتی را می‌توان به دو دسته‌ی روش‌های مبتنی بر یادگیری ماشین و روش‌های مبتنی بر ویژگی‌های دستی تقسیم‌بندی کرد. روش‌های دسته‌ی اول دارای دقت بالاتری هستند اما نیاز به حجم زیادی داده‌ی آموزش دارند. این در حالی است که در مسائلی همچون مسئله رتبه‌بندی نفوذ عامل‌ها، امکان آماده‌سازی داده‌های برچسب‌دار وجود ندارد. یکی دیگر از معایب غالب روش‌های مبتنی بر یادگیری ماشین، عدم امکان قابلیت تفسیر نتایج است. همچنین با بهره‌گیری از سازه‌های نظری مرتبط بانفوذ در شبکه‌های اجتماعی، می‌توان به مولفه‌های مؤثر در محاسبه‌ی نفوذ دست پیدا کرد. در این مقاله با تعریف شاخص‌ها و معیارهای شبکه‌ای فعالیت عامل‌ها متناسب با عملیات نفوذ، نفوذ عامل‌ها محاسبه می‌شود. در روش پیشنهادی، ابتدا مدلی جهت ارزیابی عامل با توجه به ویژگی‌های بااهمیت برای ارزیابی عملیات نفوذ معرفی شده است و سپس با مجموعه داده‌های تولیدی متناسب، ارزیابی شده است. با توجه به شاخص‌های مورد استفاده در این مدل، مجموعه دادگانی که شامل همة این شاخص‌ها باشد، وجود ندارد و ما سه مجموعه دادگان حاوی شاخص‌های مورد نظر از داده‌های توییتر تولید کردیم. نتایج به‌دست‌آمده نشانگر این مطلب است که مدل ارائه شده در کنار قابلیت تفسیرپذیری و عدم نیاز به داده‌های آموزشی، دارای عملکردی قابل مقایسه با روش‌های قبلی است. | ||
| کلیدواژه‌ها | ||
| شبکه‌های اجتماعی برخط؛ ارزیابی عملیات نفوذ؛ ارزیابی عامل‌های عملیات نفوذ | ||
| موضوعات | ||
| مدل سازی و شبیه سازی دفاع الکترونیک و سایبری | ||
| عنوان مقاله [English] | ||
| a computational model to evaluate the agent of influence operations in online social networks | ||
| نویسندگان [English] | ||
| gholamreza bazdar1؛ Mohammad Abdollahi Azgomi2 | ||
| 1PhD student, Imam Hossein University (AS), Tehran, Iran | ||
| 2Professor, University of Science and Technology, Tehran, Iran | ||
| چکیده [English] | ||
| The rapid and increasing use of online social networks among the society has provided a suitable field for the running cognitive and social influence operations. Optimal planning and implementation of influence operations depends on having a suitable framework for evaluating these operations. Evaluation of effective agents and actors in influence operations is one of the main requirements for evaluation of influence operations. On the other hand, considering the dynamics of online social networks and the ever-increasing production of mass data in it, it is necessary to use a computational approach to evaluate influence operations. Therefore, the purpose of this research is to find a computational model to evaluate the agents of influence operations in online social networks. In general, the methods of evaluating agent influence can be divided into three categories: qualitative evaluation, quantitative evaluation, and computational evaluation. Computational evaluation methods can be divided into two categories: methods based on machine learning (or deep learning) and methods based on hand-crafted features. The first category methods have higher accuracy but require a large amount of training data. Meanwhile, in issues such as ranking influence of agents, the preparation of labeled data is more complicated. Another disadvantage of methods based on machine learning is the inability to interpret the results. On the other hand, by using the theoretical structures related to influence in social networks, it is possible to achieve effective components in the calculation of influence. Meanwhile, better results can be achieved by combining theoretical and computational approaches. Therefore, in this article, we have presented a method that calculates the influence of agents by considering the network indicators and measures of agents' activity, by presenting the concept of user network power. In the proposed method, firstly, a model to evaluate the agent according to the important features for evaluating the influence operation is introduced based on the concept of network power, and then it is evaluated with the appropriate data set. According to the indicators used in this model, there is no data set that includes all these indicators, also we produced 3 data sets containing the desired indicators. The obtained results indicate that the presented model, in addition to interpretability and no need for training data, has a performance comparable to previous methods. | ||
| کلیدواژه‌ها [English] | ||
| Online social networks, influence operation evaluation, influence operation agents evaluation | ||
| مراجع | ||
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