Cyber Security Analysis: Limitations and Ensemble Tools

This report provides an in-depth analysis of cyber security, focusing on the concept of overfitting as a modeling error and its impact on data analysis. It examines the use of ensemble tools, highlighting their role in building dynamic performance models for applications and their effectiveness in combining various classification methods to achieve specific business goals. The report also addresses the future of cyber security, emphasizing the need for advanced malware defense systems and a combination of technical and social skills to combat the growing threats. It suggests that the cyber security field will continue to evolve, necessitating systematic and creative approaches to address its complexities. The report references several academic sources to support its findings.

CYBER SECURITY AND ANALYSIS
 Limitation of over fitting:
When functions are crammed together to fit in a data point where there is a limitation to it, this is
known as the over fitting which happens to be a modeling error. Under the study of data the over
fitting occurs when a complex model of data is designed to comprehend idiosyncrasies. There
are errors that are substantial when an attempt to model data close to each other with a little
inaccuracy can infect the model that decreases the predictive power (Galmarini et al. 2012). An
over fitted function always requests for more information about items being validated on the
dataset that has functions that are optimal and a function that is over fitted is less portable than a
simpler one.
 Evaluation and analysis on the use of ensemble tools:
Ensemble tools are a runtime and associated framework for building performances for
applications on the go. The evaluation showed that these dynamic performance models can be
used to support complex, resources that are highly dimensional allocation and inquiry of
performances. The results of evaluation of ensemble showed that these tools combines, specified,
simple and partial models for a good approximation. It is done to get good approximations of
applications performance models. To achieve a business goal that is particular and domain
specific the analysis of ensemble tool is necessary because this unifies different classifiers that
are desirable and improve the classification methods various ensemble approaches are introduced
(Helvik et al. 2016). The analysis on the use of ensemble tools helps domains related to it to
make right choices within the requirements that are given.

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 Future research work given time and resources:
There is an exponential growth of Internet and Social Media that has resulted in a growth of
cyber-attack which is significant. The results of this is disastrous and has various consequence.
In the cyber security field there is a need for a new and effective malware defense systems for
control measures of ever-rising risks and vulnerabilities. The future assumptions that can be
made are measures that includes the cyber security development of workforces and a
combination of technical and social skills. The cognitive metrics are to be indicative of the future
scopes to provide a roadmap. Since cyber is not a domain of the sense that is classic and has a
varying degree of domains that can be expanded and modified in the future (Mahmood, Tariq
and Uzma Afzal, 2013). The interconnections that exist in the cyber field makes it simple as well
as complex. The systematic and creativeness is highly value based assets when it comes to cyber
security.

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References:
Galmarini, S., R. Bianconi, W. Appel, E. Solazzo, S. Mosca, P. Grossi, M. Moran, K. Schere,
and S. T. Rao. "ENSEMBLE and AMET: Two systems and approaches to a harmonized,
simplified and efficient facility for air quality models development and evaluation." Atmospheric
environment 53 51-59,2012.
Helvik, Anne-Sofie, Geir Jacobsen, Siri Wennberg, Haakon Arnesen, Anders Ringdahl, and
Lillemor RM Hallberg. "Activity limitation and participation restriction in adults seeking hearing
aid fitting and rehabilitation." Disability and rehabilitation 28, no. 5 281-288, 2016.
Mahmood, Tariq, and Uzma Afzal. "Security analytics: Big data analytics for cybersecurity: A
review of trends, techniques and tools." In 2013 2nd national conference on Information
assurance (ncia), pp. 129-134. IEEE, 2013.

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