ECCouncil 312-39 Dumps Questions Answers

Log normalization is the key step that converts heterogeneous logs into a consistent, common schema so analysts and detections can reliably query and correlate events. In real SOC workflows, different sources use different field names, timestamp formats, severity labels, and value conventions (for example, “src_ip” vs “SourceIP,” “user” vs “AccountName”). Normalization standardizes these into consistent fields (time, host, user, source/destination, action, outcome), enabling rule logic and dashboards to work across vendors without constant manual translation. Log collection is simply getting logs into a central place; it does not guarantee they are usable or consistent. Log transformation is a broader term that can include parsing or enrichment, but normalization is the specific practice of mapping diverse formats into a common model. Log correlation comes after normalization; correlation links related events (e.g., failed logons + suspicious process + outbound beaconing) and depends on normalized data to work well. Since the problem is explicitly “multiple formats” and manual conversion delays investigation, the best solution is normalization to accelerate triage, reduce query complexity, and improve detection fidelity.

A Cloud Access Security Broker (CASB) is designed to provide visibility and policy enforcement for cloud application usage, especially in SaaS, and can extend controls across cloud services by monitoring access, enforcing data protection policies, and restricting risky sharing behaviors. The scenario emphasizes enforcing access policies, controlling data sharing, preventing sensitive data exposure, and supporting compliance—these are core CASB outcomes. CSPM focuses on configuration security and posture management (misconfigurations, compliance checks, policy drift) across cloud infrastructure, but it does not primarily enforce user-level access and data sharing controls inside cloud apps. CWPP protects workloads (VMs, containers, serverless) with runtime protection, vulnerability management, and threat detection at the compute layer, which is different from governing access and data sharing across SaaS/PaaS/IaaS usage. Cloud-native anomaly detection is a capability rather than the governance and policy enforcement layer described. From a SOC perspective in regulated environments, CASB helps reduce data leakage risk via controls like DLP policies, session controls, shadow IT discovery, and conditional access enforcement—matching the requirements in the question.

Human Intelligence (HUMINT) involves information gathered from people, relationships, and human behavior rather than purely technical artifacts. The scenario describes adversaries using social engineering and pretexting—building trust through conversations and manipulating employees to reveal sensitive information. The analyst is focusing on deception detection and psychological profiling, which are rooted in understanding human intent, influence tactics, and interpersonal manipulation patterns. That aligns with HUMINT, where insights may come from interviews, insider reporting, investigative findings, or controlled engagements that reveal motivations and methods that logs will not show. Threat intelligence feeds and technical threat intelligence primarily provide machine-consumable indicators, malware signatures, infrastructure data, and observed TTPs; they are valuable but not the main lens here because these attackers “rarely leave digital footprints.” OSINT is derived from publicly available sources, which can help identify personas or prior campaigns, but the core described intelligence method is interpreting human behavior and social manipulation. From a SOC standpoint, HUMINT-driven insights inform security awareness training, executive protection protocols, identity verification procedures, and “out-of-band” validation processes that reduce success of pretexting and business email compromise.