Detecting False Identity through Behavioural Patterns


Autoria(s): Shen, Qiang; Boongoen, Tossapon
Contribuinte(s)

Department of Computer Science

Advanced Reasoning Group

Data(s)

05/08/2008

05/08/2008

17/07/2008

Resumo

T. Boongoen and Q. Shen. 'Detecting False Identity through Behavioural Patterns', In Proceedings of International Crime Science Conference, British Library, London UK, 2008. Publisher's online version forthcoming.;The full text is currently unavailable in CADAIR pending approval by the publisher. Sponsorship: UK EPSRC grant EP/D057086

Combating identity fraud is prominent and urgent since false identity has become the common denominator of all serious crime. Typical approaches to detecting false identity rely on the similarity measure of text-based identity attributes, which are usually not applicable to falsely-defined and unknown identities. This paper presents a novel link-based approach that can efficiently overcome such barrier. Its experimental evaluation against well-known link-oriented and text-based methods significantly indicates the great potential towards an effective verification system.

Non peer reviewed

Identificador

Shen , Q & Boongoen , T 2008 , ' Detecting False Identity through Behavioural Patterns ' .

PURE: 77144

PURE UUID: a5ef7f24-4e3d-4362-8607-690d85ba4fd9

dspace: 2160/614

http://hdl.handle.net/2160/614

Idioma(s)

eng

Tipo

/dk/atira/pure/researchoutput/researchoutputtypes/contributiontoconference/paper

Direitos