Data survivability vs. security in information systems

A multiple objective problem formulation and solution methodology is presented to select optimal information and data storage configurations considering both data survivability and data security, as well as cost. This paper considers a situation where the information is divided into several separately stored blocks in order to mitigate the risk of unauthorized access or theft. The information can be used only if all of the blocks are accessed. To impede the information theft, the defender prefers to maximize the number of blocks. On the other hand the destruction of any block destroys the integrity of information and makes it impossible to use. To impede the information destruction, the defender prefers to maximize the number of parallel (reserve) copies of each block, regardless how many blocks in series there are. Given the set of available information storage resources, the defender must consider a multi-objective optimization problem to determine how many blocks and their copies to create, and how to distribute them among available resources in order to minimize information vulnerability, insecurity, and storage cost. Non-dominated solutions to this problem are determined using a multiple objective genetic algorithm (MOGA). This methodology is demonstrated with two general examples.