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| Section | Weight | Objectives |
|---|---|---|
| Incident Detection with SIEM | 25% | - Correlation rules and alert generation - SIEM architecture, components, and deployment models - Alert triage, prioritization, and false positive reduction - SIEM dashboards and reporting - Data ingestion, parsing, and normalization |
| Log Management | 15% | - Log normalization, correlation, and retention policies - Log sources, types, and collection methods - Events vs incidents vs logs - Centralized logging architecture |
| Forensic Investigation and Malware Analysis | 5% | - Malware types, behavior, and analysis techniques - IoC extraction and evidence handling - Digital forensics fundamentals in SOC context |
| Proactive Threat Detection | 12% | - Threat intelligence types and sources - Threat hunting methodologies and techniques - Integrating threat intelligence into SOC workflows - UEBA and advanced detection methods |
| Understanding Cyber Threats, IoCs, and Attack Methodology | 8% | - Indicators of Compromise (IoCs) and Indicators of Attack (IoAs) - Network, host, and application-level attacks - Attack frameworks and methodologies - Types of cyber threats and threat actors |
| Incident Response | 25% | - Roles and responsibilities in incident response - SOAR, EDR, XDR technologies - Documentation, reporting, and post-incident review - Incident response lifecycle and frameworks - Containment, eradication, and recovery procedures |
| SOC for Cloud Environments | 5% | - Cloud log collection and analysis - Cloud security monitoring challenges - Cloud threat detection and response |
| Security Operations and Management | 5% | - SOC implementation and operational models - SOC components: people, processes, technology - SOC fundamentals and objectives |
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NEW QUESTION # 110
A financial institution's SIEM is generating a high number of false positives, causing alert fatigue among SOC analysts. To reduce this burden and improve threat detection accuracy, the organization integrates AI capabilities into the SIEM. After implementation, the SOC team observes a significant decrease in redundant alerts, along with faster detection of genuine threats. Which AI capability contributed to this improvement?
Answer: D
Explanation:
Dynamic rule optimization best explains a reduction in false positives and redundant alerts after adding AI to a SIEM. In SOC operations, alert fatigue often comes from static thresholds, overly broad correlations, and detections that don't adapt to changing baselines (new business apps, seasonal activity, infrastructure changes). AI-driven dynamic optimization can tune thresholds, suppress noisy patterns, and adjust scoring based on context (user role, device posture, known maintenance windows, historical behavior). This reduces duplicate/low-value alerts while preserving or improving sensitivity for real threats, which aligns with
"decrease in redundant alerts" and "faster detection of genuine threats." Rule validation/testing improves quality but is usually a manual or pre-deployment activity, not a continuous adaptive capability. Automated rule generation might create new detections, but it doesn't inherently reduce noise unless paired with tuning.
Data integration enhancement improves coverage and correlation, but by itself it can increase alerts if not tuned. The described outcome-less noise, better precision, quicker true detection-matches adaptive tuning and optimization of detections over time, which is dynamic rule optimization.
NEW QUESTION # 111
Jony, a security analyst, while monitoring IIS logs, identified events shown in the figure below.
What does this event log indicate?
Answer: C
NEW QUESTION # 112
Which of the following steps of incident handling and response process focus on limiting the scope and extent of an incident?
Answer: B
NEW QUESTION # 113
Which of the following formula represents the risk?
Answer: B
Explanation:
Risk is typically calculated as the product oflikelihood, impact, and asset value. Likelihood represents the probability of a threat exploiting a vulnerability, impact refers to the potential damage or loss that could result from the threat, and asset value quantifies the importance or worth of the asset to the organization. The formula ( \text{Risk} = \text{Likelihood} \times \text{Impact} \times \text{Asset Value} ) captures the essence of risk in terms of these three factors.
References: The EC-Council's Certified SOC Analyst (CSA) programincludes training on risk assessment and management, which involves understanding how to calculate and manage risk based on various factors including likelihood, impact, and asset value. The CSA curriculum is designed to align with industry best practices and standards for security operations centers12.
NEW QUESTION # 114
Which of the following Windows event is logged every time when a user tries to access the "Registry" key?
Answer: A
NEW QUESTION # 115
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