A Distributed and Privacy-preserving Method for Network Intrusion Detection
Résumé
Organizations security becomes increasingly more difficult
to obtain due to the fact that information technology and networking
resources are dispersed across organizations. Network intrusion attacks
are more and more difficult to detect even if the most sophisticated
security tools are used. To address this problem, researchers and vendors
have proposed alert correlation, an analysis process that takes the events
produced by the monitoring components and produces compact reports
on the security status of the organization under monitoring. Centralized
solutions imply to gather from distributed resources by a third party
the global state of the network in order to evaluate risks of attacks but
neglect the honest but curious behaviors. In this paper, we focus on this
issue and propose a set of solutions able to give a coarse or a fine grain
global state depending on the system needs and on the privacy level
requested by the involved organizations.