
4.96 GB | 9min 52s | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English
Files Included :
1 11 The Problem with Manual Cyber Defense.mp4 (107.79 MB)
2 12 Why Rule-Based Automation Breaks.mp4 (75.02 MB)
3 13 AI as a Decision Engine (Not Just Detection).mp4 (90.73 MB)
4 14 Security Automation vs Orchestration.mp4 (74.5 MB)
5 15 Where Humans Should Stay in the Loop.mp4 (64.51 MB)
6 16 Automation Failure Case Studies.mp4 (57.81 MB)
7 17 Mapping Security Tasks to Automation Potential.mp4 (56.58 MB)
8 21 How AI Makes Decisions.mp4 (62.6 MB)
9 22 Patterns vs Rules vs Learning.mp4 (50.02 MB)
10 23 Supervised vs Unsupervised AI for Automation.mp4 (55.08 MB)
11 24 Confidence, Thresholds & Risk Scores.mp4 (44.33 MB)
12 25 Training AI for Operational Environments.mp4 (52.57 MB)
13 26 Why Perfect Accuracy Is Dangerous.mp4 (55.51 MB)
14 27 Practical Exercise Automation Decision Mapping.mp4 (52.84 MB)
15 31 Traditional Detection Pipelines.mp4 (51.17 MB)
16 32 AI-Driven Detection Pipelines.mp4 (48.84 MB)
17 33 Event Correlation Using AI.mp4 (43.83 MB)
18 34 Alert Deduplication & Suppression.mp4 (61.41 MB)
19 35 AI-Based Severity Scoring.mp4 (57.29 MB)
20 36 False Positive Reduction Strategies.mp4 (54.06 MB)
21 37 Practical Lab Automated Alert Prioritization.mp4 (51.93 MB)
22 41 Why Monitoring Doesn't Scale.mp4 (70.07 MB)
23 42 AI-Driven Anomaly Detection.mp4 (54.63 MB)
24 43 Behavioral Baselines & Drift.mp4 (57.27 MB)
25 44 Continuous Monitoring with AI.mp4 (64.62 MB)
26 45 Context-Aware Monitoring.mp4 (62.32 MB)
27 46 Alert Escalation Automation.mp4 (56.01 MB)
28 47 Lab Self-Adjusting Monitoring Rules.mp4 (51.91 MB)
29 51 Anatomy of a Modern SOC.mp4 (61.1 MB)
30 52 Where SOC Analysts Lose Time.mp4 (57.75 MB)
31 53 AI for Alert Triage.mp4 (55.3 MB)
32 54 Automated Case Creation & Enrichment.mp4 (51.3 MB)
33 55 Analyst Assistants vs Autonomous Agents.mp4 (66.7 MB)
34 56 Measuring SOC Automation Success.mp4 (53.5 MB)
35 57 Lab AI-Driven SOC Workflow.mp4 (60.52 MB)
36 61 Incident Response Bottlenecks.mp4 (56 MB)
37 62 AI-Assisted Incident Classification.mp4 (44.96 MB)
38 63 Automated Evidence Collection.mp4 (54.45 MB)
39 64 Decision Trees vs AI Decisions.mp4 (53.37 MB)
40 65 Automated Containment Actions.mp4 (41.95 MB)
41 66 Rollback & Human Override.mp4 (59.72 MB)
42 67 Practical Simulation Automated IR Flow.mp4 (49.46 MB)
43 71 From Detection to Defense.mp4 (58.22 MB)
44 72 Automated Blocking & Isolation.mp4 (97.8 MB)
45 73 Adaptive Firewall & Network Rules.mp4 (77.33 MB)
46 74 Endpoint Containment Automation.mp4 (77.57 MB)
47 75 Confidence-Based Defense Actions.mp4 (83.07 MB)
48 76 Avoiding Self-Inflicted Outages.mp4 (87.58 MB)
49 77 Lab Controlled Autonomous Defense.mp4 (90.37 MB)
50 81 Why Cloud Security Must Be Automated.mp4 (119.26 MB)
51 82 AI for IAM Abuse Detection.mp4 (97.12 MB)
52 83 Automated Permission Risk Scoring.mp4 (79.16 MB)
53 84 Cloud Misconfiguration Auto-Fixing.mp4 (124.85 MB)
54 85 AI-Driven Access Revocation.mp4 (111.91 MB)
55 86 Continuous Cloud Defense Loops.mp4 (97.72 MB)
56 87 Lab AI-Based Cloud Security Automation.mp4 (118.04 MB)
57 91 Network Security Automation Basics.mp4 (103.68 MB)
58 92 AI-Driven IDS & IPS.mp4 (91.24 MB)
59 93 Automated Lateral Movement Detection.mp4 (83.87 MB)
60 94 Endpoint Behavior Automation.mp4 (81.62 MB)
61 95 Deception & Moving Target Defense.mp4 (84.68 MB)
62 96 Automated Threat Containment.mp4 (66.31 MB)
63 97 Lab Network + Endpoint Automation.mp4 (63.42 MB)
64 101 When Automation Goes Wrong.mp4 (63.94 MB)
65 102 Automation Blind Spots.mp4 (71.49 MB)
66 103 Feedback Loops & Cascade Failures.mp4 (62.75 MB)
67 104 Adversarial Abuse of Automation.mp4 (54.09 MB)
68 105 Human-in-the-Loop Design.mp4 (57.15 MB)
69 106 Kill Switches & Rollback Systems.mp4 (59.63 MB)
70 111 Attacks Against AI Security Systems.mp4 (74.77 MB)
71 112 Data Poisoning in Automation Pipelines.mp4 (50.12 MB)
72 113 Model Evasion Techniques.mp4 (50 MB)
73 114 Securing Training Data.mp4 (61.44 MB)
74 115 Monitoring AI Decisions.mp4 (60.47 MB)
75 116 Trust & Explainability in Defense AI.mp4 (67.46 MB)]
Screenshot
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