- author = "Yow Tzu Lim",
- title = "Evolving Security Policies",
- school = "Computer Science, University of York",
- year = "2010",
- address = "UK",
- keywords = "genetic algorithms, genetic programming, Grammatical Evolution",
-
URL = "
http://etheses.whiterose.ac.uk/id/eprint/1612",
-
URL = "
http://etheses.whiterose.ac.uk/1612/3/thesis.pdf",
- size = "212 pages",
-
abstract = "As computer system size and complexity grow,
formulating effective policies require more
sophistication. There are many risk factors that need
to be considered, some of which may be in conflict.
Inevitably, unpredictable circumstances that demand
decisions will arise during operation. In some cases an
automated response may be imperative; in other cases
these may be ill-advised. Manual decisions are often
made that override the current policy and serve
effectively to redefine it. This matter is further
complicated in highly dynamic operational environments
like mobile ad-hoc networks, in which the risk factors
may be changing continually. Thus, security policies
must be able to change and adapt to the operational
needs. This study investigates the potential of
evolutionary algorithms as a tool in determining the
optimal security policies that suit such environments.
This thesis reviews some fundamental concepts in
related domains. It presents three applications of
evolutionary algorithms in solving problems that are of
direct relevance. These include the inference of
security policies from decision examples, the dynamic
adaptation of security policies, and the optimisation
of security policies for a specific set of missions.
The results show that the inference approaches based on
evolutionary algorithms are very promising.
The thesis concludes with an evaluation of the work done, the extent to which the work justifies the thesis hypothesis and some possible directions on how evolutionary algorithms can be applied to address a wider range of relevant problems in the domain of concern.",
- notes = "Supervisor John A. Clark",
