Business > CASE STUDY > Practical Connection Assignment.docx (1) Practical Connection Assignment University of (All)
Practical Connection Assignment.docx (1) Practical Connection Assignment University of The Cumberlands Intro to Data Mining Datamining is about the study algorithms that can allow computers to fi... nd the patterns and similarities within databases, and perform the prediction, forecasting which will help improve the performance with the interaction of data in multiple ways. Knowledge discovery is the key component for dealing with extractions of useful knowledge from raw data. It also includes the selection of data, cleaning, coding and usage of different statistical and machine learning techniques with the visualization of structures that are generated. As a Security Engineer, I work closely on identifying the potential threats with the usage different intrusion prevention and intrusion detection systems. As the network attacks have increased in number and also with severity level and Intrusion detection system. But with high volume of audits related to security and dynamic properties of intrusion, optimizing performance of the intrusion detection system. Data Mining course have helped to learn about multiple classification concepts like decision trees, model evaluation and other alternative techniques. I was also applying few concepts of data mining into our Intrusion detection system; we have used anomaly detection to help prioritize the potential threat records for review. These techniques also helped in identifying the unusual patterns of the user network traffic and also the sequential association an. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .. .. . . . . . . . . . . . . . . . . . .. . . . . [Show More]
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