On stochastic risk ordering of network services for proactive security management

Contemporary network services don't have any statistical ranking mechanism for proactive security management. Since the emerging threats are actively exploiting the vulnerabilities in network services to compromise the system, not much attention has been paid to rank these services based on their vulnerability history. We argue in this paper that a reliable mechanism could be used to rank these services based on their vulnerability history. Such ranking will be significantly helpful for proactive network security management to partition services and deploy security countermeasures. We propose a framework using stochastic order alternatives to statistically rank network services based on time intervals between exploits as reported by National Vulnerability Database (NVD). We show that Statistical techniques can be used to rank these services by modeling the related metrics. We validated our technique using products of known ranking, and presented some case studies to confirm our result on real network services.