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

Title	Detection of malicious social bots: A survey and a refined taxonomy
Author	Latah, Majd
Publication Date:	2020-08-01
Publication Place	- Elsevier
Subject	Security, Online social networks, Social bots, Taxonomy, Malicious behavior
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	0957-4174
Record ID	39bfe241-1873-4b3a-9d0c-58fe36475015
Date	2020-08-01
Sample Text	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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Özyeğin University

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

Author Latah, Majd

Publication Date 2020-08-01

Publication Place - Elsevier

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

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 0957-4174

Record ID 39bfe241-1873-4b3a-9d0c-58fe36475015

Date 2020-08-01

Sample Text 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