Abstract

Online social networks (OSNs) are increasingly threatened by social bots which are software-controlled OSN accounts that mimic human users with malicious intentions. A social botnet refers to a group of social bots under the control of a single botmaster, which collaborate to conduct malicious behavior while mimicking the interactions among normal OSN users to reduce their individual risk of being detected. We demonstrate the effectiveness and advantages of exploiting a social botnet for spam distribution and digital-influence manipulation through real experiments on Twitter and also trace-driven simulations. We also propose the corresponding countermeasures and evaluate their effectiveness. Our results can help understand the potentially detrimental effects of social botnets and help OSNs improve their bot(net) detection systems.

Original languageEnglish (US)
Article number7790819
Pages (from-to)1068-1082
Number of pages15
JournalIEEE Transactions on Dependable and Secure Computing
Volume15
Issue number6
DOIs
StatePublished - Nov 1 2018

Fingerprint

Botnet
Experiments

Keywords

  • digital influence
  • Social bot
  • social botnet
  • spam distribution

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

The rise of social botnets : Attacks and countermeasures. / Zhang, Jinxue; Zhang, Rui; Zhang, Yanchao; Yan, Guanhua.

In: IEEE Transactions on Dependable and Secure Computing, Vol. 15, No. 6, 7790819, 01.11.2018, p. 1068-1082.

Research output: Contribution to journalArticle

Zhang, Jinxue ; Zhang, Rui ; Zhang, Yanchao ; Yan, Guanhua. / The rise of social botnets : Attacks and countermeasures. In: IEEE Transactions on Dependable and Secure Computing. 2018 ; Vol. 15, No. 6. pp. 1068-1082.
@article{2f7dd72e3dcd405899a17f85dd58e641,
title = "The rise of social botnets: Attacks and countermeasures",
abstract = "Online social networks (OSNs) are increasingly threatened by social bots which are software-controlled OSN accounts that mimic human users with malicious intentions. A social botnet refers to a group of social bots under the control of a single botmaster, which collaborate to conduct malicious behavior while mimicking the interactions among normal OSN users to reduce their individual risk of being detected. We demonstrate the effectiveness and advantages of exploiting a social botnet for spam distribution and digital-influence manipulation through real experiments on Twitter and also trace-driven simulations. We also propose the corresponding countermeasures and evaluate their effectiveness. Our results can help understand the potentially detrimental effects of social botnets and help OSNs improve their bot(net) detection systems.",
keywords = "digital influence, Social bot, social botnet, spam distribution",
author = "Jinxue Zhang and Rui Zhang and Yanchao Zhang and Guanhua Yan",
year = "2018",
month = "11",
day = "1",
doi = "10.1109/TDSC.2016.2641441",
language = "English (US)",
volume = "15",
pages = "1068--1082",
journal = "IEEE Transactions on Dependable and Secure Computing",
issn = "1545-5971",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "6",

}

TY - JOUR

T1 - The rise of social botnets

T2 - Attacks and countermeasures

AU - Zhang, Jinxue

AU - Zhang, Rui

AU - Zhang, Yanchao

AU - Yan, Guanhua

PY - 2018/11/1

Y1 - 2018/11/1

N2 - Online social networks (OSNs) are increasingly threatened by social bots which are software-controlled OSN accounts that mimic human users with malicious intentions. A social botnet refers to a group of social bots under the control of a single botmaster, which collaborate to conduct malicious behavior while mimicking the interactions among normal OSN users to reduce their individual risk of being detected. We demonstrate the effectiveness and advantages of exploiting a social botnet for spam distribution and digital-influence manipulation through real experiments on Twitter and also trace-driven simulations. We also propose the corresponding countermeasures and evaluate their effectiveness. Our results can help understand the potentially detrimental effects of social botnets and help OSNs improve their bot(net) detection systems.

AB - Online social networks (OSNs) are increasingly threatened by social bots which are software-controlled OSN accounts that mimic human users with malicious intentions. A social botnet refers to a group of social bots under the control of a single botmaster, which collaborate to conduct malicious behavior while mimicking the interactions among normal OSN users to reduce their individual risk of being detected. We demonstrate the effectiveness and advantages of exploiting a social botnet for spam distribution and digital-influence manipulation through real experiments on Twitter and also trace-driven simulations. We also propose the corresponding countermeasures and evaluate their effectiveness. Our results can help understand the potentially detrimental effects of social botnets and help OSNs improve their bot(net) detection systems.

KW - digital influence

KW - Social bot

KW - social botnet

KW - spam distribution

UR - http://www.scopus.com/inward/record.url?scp=85056529130&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056529130&partnerID=8YFLogxK

U2 - 10.1109/TDSC.2016.2641441

DO - 10.1109/TDSC.2016.2641441

M3 - Article

VL - 15

SP - 1068

EP - 1082

JO - IEEE Transactions on Dependable and Secure Computing

JF - IEEE Transactions on Dependable and Secure Computing

SN - 1545-5971

IS - 6

M1 - 7790819

ER -