Table 4 Challenges of anomaly detection in context of big data problem (volume aspect)
From: A comprehensive survey of anomaly detection techniques for high dimensional big data
Characteristic features | Description | |
|---|---|---|
1. Uncertainty | Data can be uncertain due to external events from vulnerable sources, such as failing to calculate the measure of attributes, imprecision, vagueness, inconsistency, and ambiguity. Data that cannot be depended upon with complete certainty are known as uncertain [105] | |
2. Performance | The performance of the technique in terms of time and the amount of memory is vital while detecting anomalies in high-dimensional data | |
3. Scalability | It is the ability of the technique to cater the increasing dimensions and data size | |