مقاله انگلیسی رایگان در مورد تکنیک های تشخیص نمایه تقلبی در شبکه های اجتماعی آنلاین در سطح گسترده – الزویر 2018

 

مشخصات مقاله
ترجمه عنوان مقاله تکنیک های تشخیص نمایه تقلبی در شبکه های اجتماعی آنلاین در سطح گسترده: یک بررسی جامع
عنوان انگلیسی مقاله Fake profile detection techniques in large-scale online social networks: A comprehensive review
انتشار سال 2018
تعداد صفحات مقاله انگلیسی 13 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) Scopus – Master Journal List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
2.762 در سال 2018
شاخص H_index 49 در سال 2019
شاخص SJR 0.443 در سال 2018
شناسه ISSN 0045-7906
شاخص Quartile (چارک) Q2 در سال 2018
رشته های مرتبط مهندسی فناوری اطلاعات
گرایش های مرتبط اینترنت و شبکه های گسترده، سامانه های شبکه ای، شبکه های کامپیوتری
نوع ارائه مقاله
ژورنال
مجله  کامپیوتر و مهندسی برق – Computers & Electrical Engineering
دانشگاه Department of Computer Technology, MIT campus, Anna University, Chennai, 600044, India
کلمات کلیدی شناسایی نمایه جعلی، شبکه های اجتماعی آنلاین، حملات Sybil، کلان داده
کلمات کلیدی انگلیسی Fake profile detection، Online social networks، Sybil attacks، Big data
شناسه دیجیتال – doi
https://doi.org/10.1016/j.compeleceng.2017.05.020
کد محصول E11304
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract

1- Introduction

2- Research related to OSN security threats

3- Existing models

4- Recent work on privacy-preserving fake profile detection

5- Comparison of current techniques

6- Open issues

7- Conclusion

References

بخشی از متن مقاله:

Abstract

In the present era, online social networks are the most popular and rapid information propagation applications on the Internet. People of all ages spend most of their time on social networking sites. Huge volumes of data are being created and shared through social networks around the world. These interests have given rise to illegitimate users who engage in fraudulent activities against social network users. On social networks, fake profile creation is considered to cause more harm than any other form of cyber crime. This crime has to be detected even before the user is notified about the fake profile creation. Many algorithms and methods, most of which use the huge volume of unstructured data generated from social networks, have been proposed for the detection of fake profiles. This study presents a survey of the existing and latest technical work on fake profile detection.

Introduction

Social media is growing incredibly fast these days, which is important for marketing campaigns and celebrities who try to promote themselves by growing their base of followers and fans. However, fake profiles, created seemingly on behalf of organizations or people, can damage their reputations and decrease their numbers of likes and followers. They also suffer from fake updates and unnecessary confusion with other people. Fake profiles of all kinds create negative effects that counteract the advantages of social media for businesses in advertising and marketing and pave the way for cyber bullying. The users have different concerns regarding their privacy in an online environment. Fire et al. [1] described the threats of which users are unaware in Online Social Networks (OSNs). These include loss of privacy, identity theft, malware, fake profiles (Sybil’s/social bots), and sexual harassment, among others. OSNs have billions of registered users. Facebook is the most famous OSN with more than a billion active users. There are basically four kinds of threats in OSN: classic threats, modern threats, combination threats, and threats targeting children. Several suggested solutions to these threats fall into three categories: operator, commercial, and academic solutions. The mechanisms in each of these categories can help to overcome the security threats in OSNs. Social engineering [2] is the primary cause of many kinds of security and privacy threats in OSNs. The main approaches to social engineering are social-technical, technical, physical, and social, and these are generally carried out using software or humans. The channels for social engineering are e-mail, instant messenger, telephone, Voice over Internet Protocol (VoIP), OSN, cloud, websites and physical channels.

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