Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Data Mining Using Grammar-Based Genetic Programming and Applications
Data Mining Using Grammar-Based Genetic Programming and Applications
Fuzzy Multi-Level Security: An Experiment on Quantified Risk-Adaptive Access Control
SP '07 Proceedings of the 2007 IEEE Symposium on Security and Privacy
Strongly typed genetic programming
Evolutionary Computation
Dynamic security policy learning
Proceedings of the first ACM workshop on Information security governance
Risk-based adaptive security for smart IoT in eHealth
Proceedings of the 7th International Conference on Body Area Networks
| Hi-index | 0.00 |
In the early days a policy was a set of simple rules with a clear intuitive motivation that could be formalised to good effect. However the world is becoming much more complex. Subtle risk decisions may often need to be made and people are not always adept at expressing rationale for what they do. In this paper we investigate how policies can be inferred automatically using Genetic Programming (GP) from examples of decisions made. This allows us to discover a policy that may not formally have been documented, or else extract an underlying set of requirements by interpreting user decisions to posed "what if" scenarios. Three proof of concept experiments on MLS Bell-LaPadula, Budgetised MLS and Fuzzy MLS policies have been carried out. The results show this approach is promising.