Information cryptology is commonly connected with surveillance, warfare and

exists and is used in many forms including financial accounts, military and political.
The security of this information, both in storage and transit is crucial as its
compromise may result in financial loss, disclosure of military or commercial
secrets and even the loss of life. Cryptology is one set of techniques of
providing information security. Historically, cryptology is commonly connected
with surveillance, warfare and the like. However, with the advent of the
information civilization and the digital revolution, cryptology is more and
more important also in the peaceful lives of common people, e.g., when buying
something over the internet through credit card, withdraw money from the ATM
machines using smartcards and for locking system of luxury cars. In this
research, we contribute towards automation of many processes related to
cryptology that just seem to waste our time in todays rushed world, and for
this purpose, we utilize modern combinatorial search heuristics which is also
called optimization heuristics or metaheuristics. Here we emphasize that the
metaheuristics are desirable to use since it removes the need for
time-consuming (human) interaction with a search process. Combining
metaheuristics and cryptology is not a new approach since there is a significant
number of papers (and thesis) in this area. However, we introduce a novelty in
the choice of metaheuristics and problems of interest.

      Cryptology field is commonly divided into
two subfields that are not completely disjoint. Cryptography is related to the
design of cryptographic primitives and protocols. Cryptanalysis is the process
of finding flaws or oversights in the design of crypto schemes where the goal
of cryptanalyst is to systematically recover the original text (plaintext) and/or
key by mounting an attack on the cryptosystem. A common approach in cryptology
is Kerckhoffs’ principle, which states that a cryptosystem should be secure
even if everything about the system, except the key, is public knowledge. That
is, the algorithm itself should not have to be secret, only its input.

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stated that metaheuristics could not be used to solve every problem. Therefore,
we start with assessing which problems can be tackled. If the problem can be
represented as an optimization problem, and there is enough search space
information to drive the search, it should be possible to use metaheuristics
successfully. Furthermore, we also try to systematically approach the problems
of interest with respect to both the communities, i.e., cryptologic community
and evolutionary computation (EC) community. Indeed, in many projects we can
observe that people from the EC community work on cryptology-related problems.
However, for them, those problems are only benchmarks to test the strength of
the EC methods, and they never truly test (or even consider) the obtained
solutions in practical scenarios. From the other perspective, people from the
cryptology community sometimes use EC approaches and obtain poor results. In
those cases, the question is whether the poor result is a consequence of a bad
algorithm or an inappropriate usage of that algorithm. In this thesis, we
consider several cryptology-related problems, assess possible difficulties and
solve those problems with different EC methods. One can ask how to know whether
the obtained solutions are optimal. In general, we cannot be sure, but we offer
a rule of thumb: if the solution is better than the currently known, used
solutions, then it should be regarded as good enough. Therefore, we can informally
restate our goal as a search for “good enough” solutions. We leave to the interested
parties to determine what is “good enough” since this is often problem-specific.