Profiling high leverage points for detecting anomalous users in telecom data networks

• Tipo: Artigo em Revista Científica Internacional
• Data: 2020

Autores

Tabassum, S (Autor) Outra; Azad, MA (Autor) Outra; João Gama (Autor) FEP

Revista

Título: Annales des Telecommunications/Annals of Telecommunications

Vol. 75 Nº : 9-10

Páginas: 573-581

ISSN: 0003-4347

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 7 Citações

Outras Informações

ID Authenticus: P-00S-JD8

DOI: 10.1007/s12243-020-00794-z

Abstract (EN): Fraud in telephony incurs huge revenue losses and causes a menace to both the service providers and legitimate users. This problem is growing alongside augmenting technologies. Yet, the works in this area are hindered by the availability of data and confidentiality of approaches. In this work, we deal with the problem of detecting different types of unsolicited users from spammers to fraudsters in a massive phone call network. Most of the malicious users in telecommunications have some of the characteristics in common. These characteristics can be defined by a set of features whose values are uncommon for normal users. We made use of graph-based metrics to detect profiles that are significantly far from the common user profiles in a real data log with millions of users. To achieve this, we looked for the high leverage points in the 99.99th percentile, which identified a substantial number of users as extreme anomalous points. Furthermore, clustering these points helped distinguish malicious users efficiently and minimized the problem space significantly. Convincingly, the learned profiles of these detected users coincided with fraudulent behaviors.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 9