Creation and Management of Social Network Honeypots for Detecting Targeted Cyber Attacks

Abstract

Reconnaissance is the initial and essential phase of a successful advanced persistent threat (APT). In many cases, attackers collect information from social media, such as professional social networks. This information is used to select members that can be exploited to penetrate the organization. Detecting such reconnaissance activity is extremely hard because it is performed outside the organization premises. In this paper, we propose a framework for management of social network honeypots to aid in detection of APTs at the reconnaissance phase. We discuss the challenges that such a framework faces, describe its main components, and present a case study based on the results of a field trial conducted with the cooperation of a large European organization. In the case study, we analyze the deployment process of the social network honeypots and their maintenance in real social networks. The honeypot profiles were successfully assimilated into the organizational social network and received suspicious friend requests and mail messages that revealed basic indications of a potential forthcoming attack. In addition, we explore the behavior of employees in professional social networks, and their resilience and vulnerability toward social network infiltration.