Anomaly Detection: Aspects of Anomaly Detection
Expert
- 11 Videos | 54m 54s
- Includes Assessment
- Earns a Badge
Network anomalies are behaviors or activities that deviate from the norm. It is important that security professionals learn to monitor these anomalies in network traffic because the traffic could be malicious. In this 11-video course, you will explore roles that network and security professionals play in detecting and addressing anomalies. Begin by looking at different types of anomalies or outliers, such as configuration faults or a malicious presence; then take a look at benefits of anomaly detection, such as early response and planning for the unexpected. Learners will also examine the limitations of traditional approaches to anomaly detection, such as chasing false positives; learn how to differentiate between manual and automated detection techniques; and view the importance of building a profile of what is normal, such as user activity, before looking at multimodel attributes and how they relate to anomaly detection. Furthermore, you will explore differences between least frequency of occurrence and baselining; view the benefits of machine learning; and finally, learn how to recognize benefits of auto-periodicity to aid in identifying anomalies.
WHAT YOU WILL LEARN
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discover the key concepts covered in this courserecognize different anomalies or outliers, such as configuration faults or a malicious presencedescribe the benefits of anomaly detection, such as early response and planning for the unexpectedrecognize limitations of traditional approaches to anomaly detection, such as chasing false positivesdifferentiate between manual and automated detection techniquesdescribe the importance to building a profile of what is normal, such as user activity
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describe multimodal attributes and how they relate to anomaly detectiondifferentiate between least frequency of occurrence and baseliningdescribe the benefits of machine learningrecognize the benefits of using auto-periodicity to aid in identifying anomaliessummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview2m 2sUP NEXT
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2.Types of Anomalies11m 4s
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3.Benefits of Anomaly Detection6m 35s
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4.Traditional Approaches6m 10s
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5.Manual vs. Automated Detection4m 39s
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6.Baselining3m 44s
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7.Multimodal Attributes4m 42s
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8.Least Frequency of Occurrence5m 26s
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9.Machine Learning5m 52s
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10.Auto-periodicity Detection3m 47s
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11.Course Summary53s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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COURSE
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