Privacy Preserving Architectures for Collaborative Intrusion Detection

TL;DR

This paper discusses privacy-preserving architectures enabling multiple organizations to collaborate on intrusion detection by sharing threat intelligence securely, addressing privacy concerns that hinder cooperation against sophisticated cyber threats.

Contribution

It identifies real-world privacy challenges, relevant cryptographic solutions, and proposes architectures for secure collaborative intrusion detection.

Findings

Highlights privacy issues in collaborative intrusion detection

Proposes cryptographic architectures for privacy preservation

Addresses challenges in sharing threat intelligence securely

Abstract

Collaboration among multiple organizations is imperative for contemporary intrusion detection. As modern threats become well sophisticated it is difficult for organizations to defend with threat context local to their networks alone. Availability of global \emph{threat intelligence} is must for organizations to defend against modern advanced persistent threats (APTs). In order to benefit from such global context of attacks, privacy concerns continue to be of major hindrance. In this position paper we identify real world privacy problems as precise use cases, relevant cryptographic technologies and discuss privacy preserving architectures for collaborative intrusion detection.