**2.2 Fusion levels**

• Detection error trade-off (DET) showing error rates on both axes, most often on a logarithmic scale. This curve is plotted for both matching errors and

The multi-biometric system ensures greater accuracy and reliability thanks to

and attacks. It is difficult and/or impossible to steal many biometric patterns

Usually the attacker is not able to use many relevant (accurate) spoofed

When biometric input data is unavailable or unacceptable by a biometric system,

In case when one biometric modality is obstructed, other modalities of the multi-

many independent biometric features that are difficult to attack

biometric system ensure correct user identification Privacy Multi-biometric systems provide greater resistance to certain types of loopholes

(templates) stored in the biometric database

*Security and Privacy From a Legal, Ethical, and Technical Perspective*

another biometric system modality may be used

If we use only one biometric authentication system, the results obtained are not always good enough. Unimodal biometric systems using a single sensor have many limitations, such as lack of uniqueness, universality, and lack of interference level associated with the acquired data, as a result of which they are unable to provide the required level of identification/verification efficiency (**Table 1**). This is due to the fact that the reliability of the biometric modality applied is affected by the precision

The multi-biometric system can be (**Figure 3**) (a) a multi-sensor system that allows obtaining data from various sensors using one biometric feature, (b) a system with multiple algorithms processing a single biometric feature, (c) a system consolidating multiple occurrences of the same body trait, (d) a system using

decisions (**Figure 2**).

*Advantages of multi-biometric systems.*

biometrics

**Name Description**

Recognition accuracy

Continuous monitoring

Biometric data enrollment

attacks

**Table 2.**

**Figure 3.**

**180**

*Types of multi-biometric systems.*

Resistance on spoof

of a single biometric system (**Table 2**).

**2.1 Types of multi-biometric systems**

**2. Multi-biometric systems**

In multimodal biometric systems, there are a number of strategies (scenarios) for the fusion of biometric information:


**Figure 4.** *Levels of fusion. (a) Feature level fusion and (b) score/rank level fusion.*

• Rank level fusion. The classifier determines the rank of each registered biometric identity. A high position is a good indicator of a good fit (**Figure 4b**).
