Detail publikace

Development of Social Networks in Email Communication

MALINKA, K. SCHÄFER, J.

Originální název

Development of Social Networks in Email Communication

Anglický název

Development of Social Networks in Email Communication

Jazyk

en

Originální abstrakt

In this paper, we perform an empirical analysis of email traffic logs obtained from a large university to better understand the development of social networks. We analyzed data containing records of emails sent over a period of 10 months - the largest dataset we are aware of. We study the long term evolution of social networks on real world data. The initial analysis of data is followed by an exploration of existence of how social network impacts the anonymity. We describe possibilities of modeling social network and describe dynamics of their development. Based on our result we design attack of proper selection, which could cause higher successfulness of disclosure attacks.

Anglický abstrakt

In this paper, we perform an empirical analysis of email traffic logs obtained from a large university to better understand the development of social networks. We analyzed data containing records of emails sent over a period of 10 months - the largest dataset we are aware of. We study the long term evolution of social networks on real world data. The initial analysis of data is followed by an exploration of existence of how social network impacts the anonymity. We describe possibilities of modeling social network and describe dynamics of their development. Based on our result we design attack of proper selection, which could cause higher successfulness of disclosure attacks.

Dokumenty

BibTex 


@inproceedings{BUT33728,
  author="Kamil {Malinka} and Jiří {Schäfer}",
  title="Development of Social Networks in Email Communication",
  annote="In this paper, we perform an empirical analysis of email traffic logs obtained
from a large university to better understand the development of social networks.
We analyzed data containing records of emails sent over a period of 10 months -
the largest dataset we are aware of. We study the long term evolution of social
networks on real world data. The initial analysis of data is followed by an
exploration of existence of how social network impacts the anonymity. We describe
possibilities of modeling social network and describe dynamics of their
development. Based on our result we design attack of proper selection, which
could cause higher successfulness of disclosure attacks.",
  address="IEEE Computer Society",
  booktitle="The Fourth International Conference on Internet Monitoring and Protection",
  chapter="33728",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IEEE Computer Society",
  year="2009",
  month="may",
  pages="1--5",
  publisher="IEEE Computer Society",
  type="conference paper"
}