Predictive Analytics: Case Studies for Cybersecurity
Machine Learning
| Intermediate
- 10 videos | 1h 23m 44s
- Includes Assessment
- Earns a Badge
Cybersecurity is the protection of user software from maliciously-intentioned agents and parties. Cyberattacks commonly focus on critical physical infrastructures like power plants, oil refineries, and gas pipelines. For geopolitical reasons, the cybersecurity of such installations is increasingly important. In this course, explore the use of classification models when modeling cyberattacks and the evaluation metrics for classification models. Next, examine a case study where machine learning and cybersecurity attempt to detect intrusions in a gas pipeline. Finally, investigate a case study where machine learning models are used to detect and cope with malware. Upon completion, you'll be able to identify the need for AI in cybersecurity and outline the appropriate use of evaluation metrics for classification models.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this courseRecognize the need for ai in cybersecurityIdentify use cases and limitations of ai in cybersecurityRecognize the confusion matrix and accuracy metricsRecall how the precision, recall, the roc curve, and the auc metric work
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Identify the details of the gas pipeline intrusion detection case studyOutline the results of the gas pipeline intrusion detection case studyOutline the malware detection using machine learning (ml) case studyState the results of the malware detection using machine learning (ml) case studySummarize the key concepts covered in this course
IN THIS COURSE
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2m 56s
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7m 53s
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8m 18s
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7m 26s
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8m 14s
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12m 13s
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8m 23s
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12m 25s
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10m 52s
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5m 5s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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