Analyzing Data for Pattern Recognition and Mitigation
Question
An organization had several cyberattacks over the last 6 months and has tasked an engineer with looking for patterns or trends that will help the organization anticipate future attacks and mitigate them.
Which data analytic technique should the engineer use to accomplish this task?
Answers
Explanations
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https://insights.principa.co.za/4-types-of-data-analytics-descriptive-diagnostic-predictive-prescriptiveThe engineer tasked with analyzing the cyberattacks should use the predictive data analytic technique.
Predictive analytics involves analyzing historical data to identify patterns, trends, and relationships that can be used to make predictions about future events or outcomes. In the context of cyberattacks, this technique can help the organization anticipate future attacks and mitigate them before they occur.
By analyzing data such as the time of day or week that attacks occurred, the types of attacks, the specific systems or applications targeted, and the methods used by attackers, the engineer can identify patterns and trends that may indicate when and where future attacks are likely to occur. This information can then be used to develop proactive measures to prevent or mitigate these attacks.
Other data analytic techniques, such as diagnostic, qualitative, or statistical analysis, may also be useful in analyzing cyberattacks, but they may not be as effective in identifying patterns and trends that can be used for predictive purposes. Diagnostic analysis is used to identify the root causes of problems, while qualitative analysis involves examining non-numeric data such as text or images. Statistical analysis involves using mathematical models to identify relationships between different variables, which may be useful for identifying correlations between different types of cyberattacks but may not be as effective in predicting future attacks.
