Anomaly-based intrusion detection systems (IDS) are particularly effective in detecting zero-day attacks because they do not rely on known signatures, which zero-day attacks would not have. Instead, they monitor network behavior for deviations from a baseline of normal activity. This approach can identify suspicious activities that could indicate a novel or unknown threat, such as a zero-day exploit12345. These systems use various methods, including machine learning and deep learning, to detect patterns that could signify an attack, making them a robust solution against the unpredictable nature of zero-day threats12345.

References: The BCS Foundation Certificate in Information Security Management Principles emphasizes the importance of understanding different types of controls and their characteristics, including technical security controls like IDS, which are essential for managing the security of information systems6. The syllabus also covers the effectiveness of controls, which is relevant when considering the capabilities of anomaly-based IDS in the context of zero-day attack detection7.