Hunting organization-targeted socialbots

Abigail Paradise; Asaf Shabtai; Rami Puzis

doi:10.1145/2808797.2809396

Hunting organization-targeted socialbots

Abigail Paradise, Asaf Shabtai, Rami Puzis

Department of Software and Information Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

In this paper we perform cost-effectiveness analysis of strategies for monitoring the organizational social network in order to trap the attacker's profiles. We analyze attack strategies with different levels of knowledge on the employed monitoring strategies. The results demonstrate the efficacy in detecting the less sophisticated attackers and slowing down attackers that deliberately avoid the profiles being monitored.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
Editors	Jian Pei, Jie Tang, Fabrizio Silvestri
Publisher	Association for Computing Machinery, Inc
Pages	537-540
Number of pages	4
ISBN (Electronic)	9781450338547
DOIs	https://doi.org/10.1145/2808797.2809396
State	Published - 25 Aug 2015
Event	IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 - Paris, France Duration: 25 Aug 2015 → 28 Aug 2015

Publication series

Name	Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

Conference

Conference	IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
Country/Territory	France
City	Paris
Period	25/08/15 → 28/08/15

Keywords

Reconnaissance
Social network
Socialbots

ASJC Scopus subject areas

Computer Science Applications
Computer Networks and Communications

Access to Document

10.1145/2808797.2809396

Cite this

Paradise, A., Shabtai, A., & Puzis, R. (2015). Hunting organization-targeted socialbots. In J. Pei, J. Tang, & F. Silvestri (Eds.), Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 (pp. 537-540). (Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015). Association for Computing Machinery, Inc. https://doi.org/10.1145/2808797.2809396

Paradise, Abigail ; Shabtai, Asaf ; Puzis, Rami. / Hunting organization-targeted socialbots. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015. editor / Jian Pei ; Jie Tang ; Fabrizio Silvestri. Association for Computing Machinery, Inc, 2015. pp. 537-540 (Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015).

@inproceedings{2ef9154bcfb64014890a3776ff85617f,

title = "Hunting organization-targeted socialbots",

abstract = "In this paper we perform cost-effectiveness analysis of strategies for monitoring the organizational social network in order to trap the attacker's profiles. We analyze attack strategies with different levels of knowledge on the employed monitoring strategies. The results demonstrate the efficacy in detecting the less sophisticated attackers and slowing down attackers that deliberately avoid the profiles being monitored.",

keywords = "Reconnaissance, Social network, Socialbots",

author = "Abigail Paradise and Asaf Shabtai and Rami Puzis",

note = "Publisher Copyright: {\textcopyright} 2015 ACM.; IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 ; Conference date: 25-08-2015 Through 28-08-2015",

year = "2015",

month = aug,

day = "25",

doi = "10.1145/2808797.2809396",

language = "English",

series = "Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015",

publisher = "Association for Computing Machinery, Inc",

pages = "537--540",

editor = "Jian Pei and Jie Tang and Fabrizio Silvestri",

booktitle = "Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015",

}

Paradise, A, Shabtai, A & Puzis, R 2015, Hunting organization-targeted socialbots. in J Pei, J Tang & F Silvestri (eds), Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Association for Computing Machinery, Inc, pp. 537-540, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Paris, France, 25/08/15. https://doi.org/10.1145/2808797.2809396

Hunting organization-targeted socialbots. / Paradise, Abigail; Shabtai, Asaf ; Puzis, Rami.
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015. ed. / Jian Pei; Jie Tang; Fabrizio Silvestri. Association for Computing Machinery, Inc, 2015. p. 537-540 (Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Hunting organization-targeted socialbots

AU - Paradise, Abigail

AU - Shabtai, Asaf

AU - Puzis, Rami

PY - 2015/8/25

Y1 - 2015/8/25

N2 - In this paper we perform cost-effectiveness analysis of strategies for monitoring the organizational social network in order to trap the attacker's profiles. We analyze attack strategies with different levels of knowledge on the employed monitoring strategies. The results demonstrate the efficacy in detecting the less sophisticated attackers and slowing down attackers that deliberately avoid the profiles being monitored.

AB - In this paper we perform cost-effectiveness analysis of strategies for monitoring the organizational social network in order to trap the attacker's profiles. We analyze attack strategies with different levels of knowledge on the employed monitoring strategies. The results demonstrate the efficacy in detecting the less sophisticated attackers and slowing down attackers that deliberately avoid the profiles being monitored.

KW - Reconnaissance

KW - Social network

KW - Socialbots

UR - http://www.scopus.com/inward/record.url?scp=84962486765&partnerID=8YFLogxK

U2 - 10.1145/2808797.2809396

DO - 10.1145/2808797.2809396

M3 - Conference contribution

AN - SCOPUS:84962486765

T3 - Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

SP - 537

EP - 540

BT - Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

A2 - Pei, Jian

A2 - Tang, Jie

A2 - Silvestri, Fabrizio

PB - Association for Computing Machinery, Inc

T2 - IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

Y2 - 25 August 2015 through 28 August 2015

ER -

Paradise A, Shabtai A , Puzis R. Hunting organization-targeted socialbots. In Pei J, Tang J, Silvestri F, editors, Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015. Association for Computing Machinery, Inc. 2015. p. 537-540. (Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015). doi: 10.1145/2808797.2809396

Hunting organization-targeted socialbots

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this