PROJECT TITLE :

A Scalable Approach to Joint Cyber Insurance and Security-asa-Service Provisioning in Cloud Computing - 2017

ABSTRACT:

As computing services are increasingly cloud-based, firms are investing in cloud-primarily based security measures. The safety-asa- Service (SECaaS) paradigm allows customers to outsource security to the cloud, through the payment of a subscription fee. However, no security system is bulletproof, and even one successful attack will end in the loss of data and revenue value many greenbacks. To protect against this eventuality, customers could additionally purchase cyber insurance to receive recompense within the case of loss. To attain cost effectiveness, it's necessary to balance provisioning of security and insurance, even when future costs and risks are unsure. To the current finish, we have a tendency to introduce a stochastic optimization model to optimally provision security and insurance services within the cloud. Since the model we design is a mixed integer problem, we tend to additionally introduce a partial Lagrange multiplier algorithm that takes advantage of the whole unimodularity property to search out the solution in polynomial time. We additionally apply sensitivity analysis to find the precise tolerance of decision variables to parameter changes. We have a tendency to show the effectiveness of these techniques using numerical results based mostly on real attack information to demonstrate a sensible testing surroundings, and realize that security and insurance are interdependent.