ID Problem Formulation

(1) Since I formulated the ID as stochastic DP problem. It owns
properties
of dynamic.
(2) To handle large state space and unknown attack type, the DP problem
transformed into adaptive tuning problem. Adaptiveness in terms of tunning
the networks interactively.

The properties of problem formulation has been addressed in the problem
formulation section. I have mathematical proof for the above items. It has been
further addressed in the methodology section of the formal paper.

As for the time constraints, do you mean I need time to implement the
entire mathematical framework as a software ? If so, it is true that I need to implement it
myself since existing tools such as MatLab only handle traditional weights tuning for fixed
neuro networks. In addition, no RL toolbox yet. This research counts on my own implementation for proposed algorithmic operations. As for the dataset preprocessing, it will not be issue for
me since I/O formating is ok for me.

False alarm ratio is only evaluated from known attacks from research
point of review. In real time system operation, it can not be proved by research framework.
This is the motivation 67to come up with "Tuning" framework for online detection in order to
reduce the false alarm ratio.Hence, false alarm problem is relaxed as the problem of "Tuning" of DP 5tproblem. This is one 1of the major advantagesyt of this research proposal.

Dataset is only critical for traditional neuro learning but not this
research. parameter is not restricted for this research either. All these are traditional neuro
learning problem. That is 238x3ethe motivation to propose RL based "Tuning" framework. This is one of major advantages of this
research proposal. For the specific host and network attack (spoofing
and memory overflow)
I have mathematical proof for this research. For the implementation, I
have to start with arbitrary
parameters and architecture. It is important to know that there is no
readily training set of state
and ROC function in DP context. The possible way is to evaluate the ROC
function by simulation
state decisions. Afterwards, using RL based interactive algorithm to
improve the ROC value. That
is the most key point of the research design.