יובל אלוביץ

אקדמי בכיר

Stealing reality

When criminals become data scientists (or vice versa)

Yaniv Altshuler, Nadav Aharony, Yuval Elovici, Alex Pentland, Manuel Cebrian

In this paper, we discuss the threat of malware targeted at extracting information about the relationships in a real-world social network as well as characteristic information about the individuals in the network, a type of attack which we dub Stealing Reality. We explain how Stealing Reality attacks differ from traditional types of attacks against individuals' privacy and discuss why their impact is significantly more dangerous than that of other attacks such as identity theft. We then analyze this new form of attack and show what an optimal attack strategy would look like. Surprisingly, it differs significantly from many conventional network attacks in that it involves extremely slow spreading patterns. We point out that besides yielding the best outcome for the attackers, such an attack may also deceive existing monitoring tools because of its low traffic volumes and the fact that it imitates natural end-user communication patterns.

שפת פרסום אנגלית
דפים 133-151
סטטוס פרסום פורסם - 01.01.2013

ASJC Scopus subject areas

General Computer Science
גישה למסמך
10.1007/978-1-4614-4139-7_7
קבצים וקישורים אחרים
Link to publication in Scopus