Explain how the principles of science relate to cybersecurity. 

Relativism is the concept that all things are related. Looking at it through cybersecurity perspective this means technology drives change in every sector. A new operating system or application is released, meaning we must adjust our tactics. It may change our policies, processes, or budget.  

Objectivity is the concept that scientists should study topics in a value-free manner. As a cybersecurity professional it is our duty to be objective. We have many heated and complex issues to address that we must withhold our opinions on. Some of these issues include monitoring a users’ traffic and information under the Patriot Act or monitoring social media for extremist activity. Topics like these tend to be hotly contested but it is important we keep a neutral and open mind. 

Parsimony is explaining things in the simplest terms possible. This was very important for me when I worked as an IT in the Navy. I spent a majority of my time on the ship as the only IT on board reporting to people with very little knowledge about my craft. The ability to explain cybersecurity concepts to people with little understanding of said concepts is one of the most important skills an IT can have. 

Empiricism is built open our experiences. How do we advance our field and abilities as cyber security? It comes from our knowledge. From a technician standpoint you grow by learning from everything you’ve done good or bad. From an organizational standpoint being able to analyze events and build policies around them will help stay ahead of the curve. 

Ethical neutrality means we must maintain ethical standards when doing research. In the scope of cybersecurity we have to ask ourselves where the line is for preventing cyber crime. How invasive can we be when collecting data? Can we reduce internet access to people we think are conducting shady practices? Where is the ethical line on these issues? 

Determinism is the theory that actions are caused by preceding events.  Determinism can relate to the predictability of systems and users and the events that happen. We can learn as ITs by pay attention to these predictable events and comparing them to the anomalies to better prepare for future events. 

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