Detection of malicious social bots: A survey and a refined taxonomy

Name: Detection of malicious social bots: A survey and a refined taxonomy
Author: Latah, Majd

İsim	Detection of malicious social bots: A survey and a refined taxonomy
Yazar	Latah, Majd
Basım Tarihi:	2020-08-01
Basım Yeri	- Elsevier
Konu	Security, Online social networks, Social bots, Taxonomy, Malicious behavior
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0957-4174
Kayıt Numarası	39bfe241-1873-4b3a-9d0c-58fe36475015
Tarih	2020-08-01
Örnek Metin	Social hots represent a new generation of hots that make use of online social networks (OSNs) as command and control (C&C) channels. Malicious social hots have been used as tools for launching large-scale spam campaigns, promoting low-cap stocks, manipulating users' digital influence, and conducting political astroturfing. Recent studies in this area either focus only on general security issues related to social networks or on coarse-grained categorization to support detection approaches. This survey aims to provide a comprehensive analysis from a social network perspective. To this end, we first categorize social bot attacks at different stages, then provide an overview of different types of social hots. Next, we propose a refined taxonomy that shows how different techniques within a category are related or differ from each other, followed by a detailed discussion of the strengths and limitations of each method. Following this, we review the existing datasets and summarize the results of empirical investigations. Finally, we highlight the limitations of existing detection approaches and suggest future directions for further improvement. Our study should help OSN administrators and researchers understand the destructive potential of malicious social hots and improve upon the current defensive strategies.
DOI	10.1016/j.eswa.2020.113383
Cilt	151

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Detection of malicious social bots: A survey and a refined taxonomy

Yazar Latah, Majd

Basım Tarihi 2020-08-01

Basım Yeri - Elsevier

Konu Security, Online social networks, Social bots, Taxonomy, Malicious behavior

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0957-4174

Kayıt Numarası 39bfe241-1873-4b3a-9d0c-58fe36475015

Tarih 2020-08-01

Örnek Metin Social hots represent a new generation of hots that make use of online social networks (OSNs) as command and control (C&C) channels. Malicious social hots have been used as tools for launching large-scale spam campaigns, promoting low-cap stocks, manipulating users' digital influence, and conducting political astroturfing. Recent studies in this area either focus only on general security issues related to social networks or on coarse-grained categorization to support detection approaches. This survey aims to provide a comprehensive analysis from a social network perspective. To this end, we first categorize social bot attacks at different stages, then provide an overview of different types of social hots. Next, we propose a refined taxonomy that shows how different techniques within a category are related or differ from each other, followed by a detailed discussion of the strengths and limitations of each method. Following this, we review the existing datasets and summarize the results of empirical investigations. Finally, we highlight the limitations of existing detection approaches and suggest future directions for further improvement. Our study should help OSN administrators and researchers understand the destructive potential of malicious social hots and improve upon the current defensive strategies.

DOI 10.1016/j.eswa.2020.113383

Cilt 151