FCSS: Fog-Computing-based Content-Aware Filtering for Security Services in Information-Centric Social Networks

Social networks are very important social cyberspaces for people. Currently, information-centric networks (ICN) are the main trend of next-generation networks, which promote traditional social networks to information-centric social networks (IC-SN). Because of the complexity and openness of social networks, the filtering of security services for users is a key issue. However, existing schemes were proposed for traditional social networks and cannot satisfy the new requirements of IC-SN including extendibility, data mobility, use of non-IP addresses, and flexible deployment. To address this challenge, a fog-computing-based content-aware filtering method for security services, FCSS, is proposed in information centric social networks. In FCSS, the assessment and content-matching schemes and the fog-computing-based content-aware filtering scheme is proposed for security services in IC-SN. FCSS contributes to IC-SN as follows. First, fog computing is introduced into IC-SN to shifting intelligence and resources from remote servers to network edge, which provides low-latency for security service filtering and end to end communications. Second, content-label technology based efficient content-aware filtering scheme is adapted for edge of IN-SN to realize accurate filtering for security services. The simulations and evaluations show the advantages of FCSS in terms of hit ratio, filtering delay, and filtering accuracy.