Explanation:
A statistical anomaly-based intrusion detection system (stat IDS) collects data from normal traffic and establishes a baseline. It then periodically samples the network activity based on statistical methods and compares samples to the baseline. When the activity is outside the baseline parameter (clipping level), the IDS notifies the administrator. The baseline variables can include a host’s memory or central processing unit (CPU) usage, network packet types and packet quantities. If actions of the users or the systems on the network vary widely with periods of low activity and periods of frantic packet exchange, a stat IDS may not be suitable, as the dramatic swing from one level to another almost certainly will generate false alarms. This weakness will have the largest impact on the operation of the IT systems. Due to the nature of stat IDS operations (i.e., they must constantly attempt to match patterns of activity to the baseline parameters), a stat IDS requires much more overhead and processing than signature-based versions. Due to the nature of a stat IDS — based on statistics and comparing data with baseline parameters — this type of IDS may not detect minor changes to system variables and may generate many false positives. Choice D is incorrect; since the stat IDS can monitor multiple system variables, it can detect new types of variables by tracing for abnormal activity of any kind.