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Finally, one of the most important requirements this software should satisfy is a real-time risk
management. As it is known, risk management is the identification, assessment, and
prioritization of risks followed by coordinated and economical application of resources to
minimize, monitor, and control the probability and/or impact of unfortunate events or to
maximize the realization of opportunities. The imperative here is to provide all this using a
solution which is able to operate in the real-time.

An Adaptive Algorithm Concept

As it was mentioned before, it could be technically possible to obtain an intelligence-led
(security) software using an adaptive algorithm concept. Here we would try to do a brief
overview of that concept.

An adaptive algorithm is a set of instructions to perform a function that can adapt in the
event of changes in environment or circumstances. Adaptive algorithms are able to
intelligently adjust their activities in light of changing circumstances to achieve the best
possible outcome.

They can be programmed in a number of computing languages to do everything from
automating air traffic control to returning search results that will be accurate and helpful for
an Internet user. It is an algorithm that changes its behavior based on information available
at the time it is run. This might be information about computational resources available, or
the history of data recently received.

The adaptive algorithm can change its behavior if it senses a necessity to do so. One of the
best examples of this algorithm is a search engine in which the engine can crawl the entire
Internet and return results from a variety of locations, but it might consider known
parameters about the user first.

Algorithms can also learn from the behavior of users. Users of the same search engine in
the same country may notice that they get different results. These are based on past search
behaviors and click-through links. The algorithm can customize its results to the needs of the
user.

For example, as implemented by some programming languages, stable partition is adaptive
and so it acquires as much memory as it can get and applies the algorithm using that
available memory. Another example is adaptive sort, whose behavior changes upon the
presortedness of its input.

In machine learning and optimization, for instance, many algorithms are adaptive or have
adaptive variants, which usually means that the algorithm parameters are automatically
adjusted according to statistics about the optimization thus far. Examples include adaptive
simulated annealing, adaptive coordinate descent, AdaBoost, and adaptive quadrature.

Additionally, in data compression, adaptive coding algorithms such as Adaptive Huffman
coding or Prediction by partial matching can take a stream of data as input, and adapt their
compression technique based on the symbols that they have already encountered.

16 Cyber Warnings E-Magazine – April 2014 Edition
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