On analyzing and evaluating privacy measures for social networks under active attack

Bhaskar DasGupta, Nasim Mobasheri, Ismael G. Yero

Research output: Contribution to journalArticle

Abstract

Widespread usage of complex interconnected social networks such as Facebook, Twitter and LinkedIn in modern internet era has also unfortunately opened the door for privacy violation of users of such networks by malicious entities. In this article we investigate, both theoretically and empirically, privacy violation measures of large networks under active attacks that was recently introduced in Trujillo-Rasua and Yero (2016). Our theoretical result indicates that the network manager responsible for prevention of privacy violation must be very careful in designing the network if its topology does not contain a cycle. Our empirical results shed light on privacy violation properties of eight real social networks as well as a large number of synthetic networks generated by both the classical Erdös–Rényi model and the scale-free random networks generated by the Barábasi–Albert preferential-attachment model.

LanguageEnglish (US)
Pages87-100
Number of pages14
JournalInformation Sciences
Volume473
DOIs
StatePublished - Jan 1 2019

Fingerprint

Social Networks
Privacy
Attack
Managers
Topology
Internet
Preferential Attachment
Random Networks
Scale-free Networks
Erdös
Social networks
Cycle
Violations
Model

Keywords

  • Active attack
  • Empirical evaluation
  • Privacy measure
  • Social networks

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

Cite this

On analyzing and evaluating privacy measures for social networks under active attack. / DasGupta, Bhaskar; Mobasheri, Nasim; Yero, Ismael G.

In: Information Sciences, Vol. 473, 01.01.2019, p. 87-100.

Research output: Contribution to journalArticle

@article{1ce7c95575354ce98354bb774af67134,
title = "On analyzing and evaluating privacy measures for social networks under active attack",
abstract = "Widespread usage of complex interconnected social networks such as Facebook, Twitter and LinkedIn in modern internet era has also unfortunately opened the door for privacy violation of users of such networks by malicious entities. In this article we investigate, both theoretically and empirically, privacy violation measures of large networks under active attacks that was recently introduced in Trujillo-Rasua and Yero (2016). Our theoretical result indicates that the network manager responsible for prevention of privacy violation must be very careful in designing the network if its topology does not contain a cycle. Our empirical results shed light on privacy violation properties of eight real social networks as well as a large number of synthetic networks generated by both the classical Erd{\"o}s–R{\'e}nyi model and the scale-free random networks generated by the Bar{\'a}basi–Albert preferential-attachment model.",
keywords = "Active attack, Empirical evaluation, Privacy measure, Social networks",
author = "Bhaskar DasGupta and Nasim Mobasheri and Yero, {Ismael G.}",
year = "2019",
month = "1",
day = "1",
doi = "10.1016/j.ins.2018.09.023",
language = "English (US)",
volume = "473",
pages = "87--100",
journal = "Information Sciences",
issn = "0020-0255",
publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - On analyzing and evaluating privacy measures for social networks under active attack

AU - DasGupta, Bhaskar

AU - Mobasheri, Nasim

AU - Yero, Ismael G.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Widespread usage of complex interconnected social networks such as Facebook, Twitter and LinkedIn in modern internet era has also unfortunately opened the door for privacy violation of users of such networks by malicious entities. In this article we investigate, both theoretically and empirically, privacy violation measures of large networks under active attacks that was recently introduced in Trujillo-Rasua and Yero (2016). Our theoretical result indicates that the network manager responsible for prevention of privacy violation must be very careful in designing the network if its topology does not contain a cycle. Our empirical results shed light on privacy violation properties of eight real social networks as well as a large number of synthetic networks generated by both the classical Erdös–Rényi model and the scale-free random networks generated by the Barábasi–Albert preferential-attachment model.

AB - Widespread usage of complex interconnected social networks such as Facebook, Twitter and LinkedIn in modern internet era has also unfortunately opened the door for privacy violation of users of such networks by malicious entities. In this article we investigate, both theoretically and empirically, privacy violation measures of large networks under active attacks that was recently introduced in Trujillo-Rasua and Yero (2016). Our theoretical result indicates that the network manager responsible for prevention of privacy violation must be very careful in designing the network if its topology does not contain a cycle. Our empirical results shed light on privacy violation properties of eight real social networks as well as a large number of synthetic networks generated by both the classical Erdös–Rényi model and the scale-free random networks generated by the Barábasi–Albert preferential-attachment model.

KW - Active attack

KW - Empirical evaluation

KW - Privacy measure

KW - Social networks

UR - http://www.scopus.com/inward/record.url?scp=85053787383&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85053787383&partnerID=8YFLogxK

U2 - 10.1016/j.ins.2018.09.023

DO - 10.1016/j.ins.2018.09.023

M3 - Article

VL - 473

SP - 87

EP - 100

JO - Information Sciences

T2 - Information Sciences

JF - Information Sciences

SN - 0020-0255

ER -