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Luiz H. Gomes

Publications and source records attributed to Luiz H. Gomes.

3 recordsLinked to original sources

Quantifying social vs. antisocial behavior in email networks

Email graphs have been used to illustrate general properties of social networks of communication and collaboration. However, increasingly, the majority of email traffic reflects opportunistic, rather than symbiotic social relations. Here we use e-mail data drawn from a large university to construct directed graphs of email exchange that quantify the differences between social and antisocial behaviors in networks of communication. We show that while structural characteristics typical of other social networks are shared to a large extent by the legitimate component they are not characteristic of antisocial traffic. Interestingly, opportunistic patterns of behavior do create nontrivial graphs with certain general characteristics that we identify. To complement the graph analysis, which suffers from incomplete knowledge of users external to the domain, we study temporal patterns of communication to show that the dynamical properties of email traffic can, in principle, distinguish different types of social relations.

physics.soc-ph↗

Improving Spam Detection Based on Structural Similarity

We propose a new detection algorithm that uses structural relationships between senders and recipients of email as the basis for the identification of spam messages. Users and receivers are represented as vectors in their reciprocal spaces. A measure of similarity between vectors is constructed and used to group users into clusters. Knowledge of their classification as past senders/receivers of spam or legitimate mail, comming from an auxiliary detection algorithm, is then used to label these clusters probabilistically. This knowledge comes from an auxiliary algorithm. The measure of similarity between the sender and receiver sets of a new message to the center vector of clusters is then used to asses the possibility of that message being legitimate or spam. We show that the proposed algorithm is able to correct part of the false positives (legitimate messages classified as spam) using a testbed of one week smtp log.

cs.CR↗

Comparative Graph Theoretical Characterization of Networks of Spam and Legitimate Email

Email is an increasingly important and ubiquitous means of communication, both facilitating contact between private individuals and enabling rises in the productivity of organizations. However the relentless rise of automatic unauthorized emails, a.k.a. spam is eroding away much of the attractiveness of email communication. Most of the attention dedicated to date to spam detection has focused on the content of the emails or on the addresses or domains associated with spam senders. Although methods based on these - easily changeable - identifiers work reasonably well they miss on the fundamental nature of spam as an opportunistic relationship, very different from the normal mutual relations between senders and recipients of legitimate email. Here we present a comprehensive graph theoretical analysis of email traffic that captures these properties quantitatively. We identify several simple metrics that serve both to distinguish between spam and legitimate email and to provide a statistical basis for models of spam traffic.

physics.soc-ph↗