The uncertainty of identity toolset: analysing digital traces for user profiling

Muhammad Adnan, Antonio Lima, Luca Rossi, Suresh Veluru, Paul Longley, Mirco Musolesi, Muttukrishnan Rajarajan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

People manage a spectrum of identities in cyber domains. Profiling individuals and assigning them to distinct groups or classes have potential applications in targeted services, online fraud detection, extensive social sorting, and cyber-security. This paper presents the Uncertainty of Identity Toolset, a framework for the identification and profiling of users from their social media accounts and e-mail addresses. More specifically, in this paper we discuss the design and implementation of two tools of the framework. The Twitter Geographic Profiler tool builds a map of the ethno-cultural communities of a person's friends on Twitter social media service. The E-mail Address Profiler tool identifies the probable identities of individuals from their e-mail addresses and maps their geographical distribution across the UK. To this end, this paper presents a framework for profiling the digital traces of individuals.

Original languageEnglish
Title of host publicationSIN '14 : proceedings of the 7th international conference on Security of Information and Networks
Place of PublicationNew York, NY
PublisherACM
Pages254-260
Number of pages7
ISBN (Print)978-1-4503-3033-6
DOIs
Publication statusPublished - 9 Sep 2014
Event7th international conference on Security of Information and Networks - Glasgow, United Kingdom
Duration: 9 Sep 201411 Sep 2014

Conference

Conference7th international conference on Security of Information and Networks
CountryUnited Kingdom
CityGlasgow
Period9/09/1411/09/14

Fingerprint

Geographical distribution
Electronic mail
Sorting
Uncertainty

Keywords

  • geographic distribution
  • identity
  • online social networks
  • substring matching
  • suffix tree
  • Twitter

Cite this

Adnan, M., Lima, A., Rossi, L., Veluru, S., Longley, P., Musolesi, M., & Rajarajan, M. (2014). The uncertainty of identity toolset: analysing digital traces for user profiling. In SIN '14 : proceedings of the 7th international conference on Security of Information and Networks (pp. 254-260). New York, NY: ACM. https://doi.org/10.1145/2659651.2659741
Adnan, Muhammad ; Lima, Antonio ; Rossi, Luca ; Veluru, Suresh ; Longley, Paul ; Musolesi, Mirco ; Rajarajan, Muttukrishnan. / The uncertainty of identity toolset : analysing digital traces for user profiling. SIN '14 : proceedings of the 7th international conference on Security of Information and Networks. New York, NY : ACM, 2014. pp. 254-260
@inproceedings{b3af7cd7ac3e4bc081f7511c6e48e5d7,
title = "The uncertainty of identity toolset: analysing digital traces for user profiling",
abstract = "People manage a spectrum of identities in cyber domains. Profiling individuals and assigning them to distinct groups or classes have potential applications in targeted services, online fraud detection, extensive social sorting, and cyber-security. This paper presents the Uncertainty of Identity Toolset, a framework for the identification and profiling of users from their social media accounts and e-mail addresses. More specifically, in this paper we discuss the design and implementation of two tools of the framework. The Twitter Geographic Profiler tool builds a map of the ethno-cultural communities of a person's friends on Twitter social media service. The E-mail Address Profiler tool identifies the probable identities of individuals from their e-mail addresses and maps their geographical distribution across the UK. To this end, this paper presents a framework for profiling the digital traces of individuals.",
keywords = "geographic distribution, identity, online social networks, substring matching, suffix tree, Twitter",
author = "Muhammad Adnan and Antonio Lima and Luca Rossi and Suresh Veluru and Paul Longley and Mirco Musolesi and Muttukrishnan Rajarajan",
year = "2014",
month = "9",
day = "9",
doi = "10.1145/2659651.2659741",
language = "English",
isbn = "978-1-4503-3033-6",
pages = "254--260",
booktitle = "SIN '14 : proceedings of the 7th international conference on Security of Information and Networks",
publisher = "ACM",
address = "United States",

}

Adnan, M, Lima, A, Rossi, L, Veluru, S, Longley, P, Musolesi, M & Rajarajan, M 2014, The uncertainty of identity toolset: analysing digital traces for user profiling. in SIN '14 : proceedings of the 7th international conference on Security of Information and Networks. ACM, New York, NY, pp. 254-260, 7th international conference on Security of Information and Networks, Glasgow, United Kingdom, 9/09/14. https://doi.org/10.1145/2659651.2659741

The uncertainty of identity toolset : analysing digital traces for user profiling. / Adnan, Muhammad; Lima, Antonio; Rossi, Luca; Veluru, Suresh; Longley, Paul; Musolesi, Mirco; Rajarajan, Muttukrishnan.

SIN '14 : proceedings of the 7th international conference on Security of Information and Networks. New York, NY : ACM, 2014. p. 254-260.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - The uncertainty of identity toolset

T2 - analysing digital traces for user profiling

AU - Adnan, Muhammad

AU - Lima, Antonio

AU - Rossi, Luca

AU - Veluru, Suresh

AU - Longley, Paul

AU - Musolesi, Mirco

AU - Rajarajan, Muttukrishnan

PY - 2014/9/9

Y1 - 2014/9/9

N2 - People manage a spectrum of identities in cyber domains. Profiling individuals and assigning them to distinct groups or classes have potential applications in targeted services, online fraud detection, extensive social sorting, and cyber-security. This paper presents the Uncertainty of Identity Toolset, a framework for the identification and profiling of users from their social media accounts and e-mail addresses. More specifically, in this paper we discuss the design and implementation of two tools of the framework. The Twitter Geographic Profiler tool builds a map of the ethno-cultural communities of a person's friends on Twitter social media service. The E-mail Address Profiler tool identifies the probable identities of individuals from their e-mail addresses and maps their geographical distribution across the UK. To this end, this paper presents a framework for profiling the digital traces of individuals.

AB - People manage a spectrum of identities in cyber domains. Profiling individuals and assigning them to distinct groups or classes have potential applications in targeted services, online fraud detection, extensive social sorting, and cyber-security. This paper presents the Uncertainty of Identity Toolset, a framework for the identification and profiling of users from their social media accounts and e-mail addresses. More specifically, in this paper we discuss the design and implementation of two tools of the framework. The Twitter Geographic Profiler tool builds a map of the ethno-cultural communities of a person's friends on Twitter social media service. The E-mail Address Profiler tool identifies the probable identities of individuals from their e-mail addresses and maps their geographical distribution across the UK. To this end, this paper presents a framework for profiling the digital traces of individuals.

KW - geographic distribution

KW - identity

KW - online social networks

KW - substring matching

KW - suffix tree

KW - Twitter

UR - http://www.scopus.com/inward/record.url?scp=84938698774&partnerID=8YFLogxK

U2 - 10.1145/2659651.2659741

DO - 10.1145/2659651.2659741

M3 - Conference contribution

AN - SCOPUS:84938698774

SN - 978-1-4503-3033-6

SP - 254

EP - 260

BT - SIN '14 : proceedings of the 7th international conference on Security of Information and Networks

PB - ACM

CY - New York, NY

ER -

Adnan M, Lima A, Rossi L, Veluru S, Longley P, Musolesi M et al. The uncertainty of identity toolset: analysing digital traces for user profiling. In SIN '14 : proceedings of the 7th international conference on Security of Information and Networks. New York, NY: ACM. 2014. p. 254-260 https://doi.org/10.1145/2659651.2659741