Pass the IIBA Cybersecurity Analysis IIBA-CCA Questions and answers with ExamsMirror

The GDPR establishes a regulatory penalty framework intended to make privacy and data-protection obligations enforceable across organizations of any size. Under GDPR, the most severe administrative fines can reachup to €20 million or up to 4% of the organization’s total worldwide annual turnover of the preceding financial year, whichever is higher. That “whichever is greater” clause is critical: it prevents large enterprises from treating privacy violations as a minor cost of doing business and ensures the sanction can scale with the organization’s economic size and risk impact.

Cybersecurity governance and risk documents typically emphasize GDPR as a driver for enterprise risk management because the consequences extend beyond monetary fines. A confirmed violation often triggers regulatory investigations, mandatory corrective actions, and potential restrictions on processing activities. Organizations may also face indirect impacts such as breach notification costs, legal claims from affected individuals, reputational harm, loss of customer trust, and increased oversight by regulators and auditors.

From a controls perspective, GDPR penalties reinforce the need for strong security and privacy-by-design practices: data minimization, lawful processing, documented purposes, retention controls, encryption where appropriate, access control and least privilege, monitoring and incident response readiness, and evidence-based accountability through policies, records, and audit trails. Selecting option C correctly reflects GDPR’s maximum fine structure and its risk-based deterrence model.

In NIST-style risk assessment,overall likelihoodis not a single guess; it is derived by considering two related likelihood components. First isthe likelihood that a threat event will be initiated. This reflects how probable it is that a threat actor or source will attempt the attack or that a threat event will occur, considering factors such as adversary capability, intent, targeting, opportunity, and environmental conditions. Second isthe likelihood that an initiated event will succeed, meaning the attempt results in the adverse outcome. This depends heavily on the organization’s existing protections and conditions, including control strength, system exposure, vulnerabilities, misconfigurations, detection and response capability, and user behavior.

Option A matches this structure: analysts evaluate bothattack initiation likelihoodandinitiated attack success likelihoodto reach an overall view of likelihood. A high initiation likelihood with low success likelihood might occur when an organization is frequently targeted but has strong defenses. Conversely, low initiation likelihood with high success likelihood might apply to niche systems that are rarely targeted but poorly protected.

The other options are incomplete or misplaced. Risk impact is a separate dimension from likelihood, and mitigation strategy is an output of risk treatment, not an input to likelihood. Site traffic and commerce volume can influence exposure but do not define likelihood by themselves. Past experience and trends are useful evidence, but they support estimating the two likelihood components rather than replacing them.