Multifactor Authentication

Authentication can be accomplished with one factor, two factors, or multiple factors. Which one is the weakest level of authentication and which is the most secure and why? When would a more secure system be required? Be able to explain these multifactor authentication methods: password protection, token presence, voice biometrics, facial recognition, ocular-based methodology, hand geometry, vein recognition, fingerprint scanner, thermal image recognition, and geographical location. What are some challenges of multiple factor authentication when using biometrics? There is a lot of interesting information covered in this article that you do not need to memorize, but that you should be aware of.

2. State-of-the-Art and Potential MFA Sources

2.2.6. DNA Recognition

Human cell lines are an essential resource for research, which is most frequently used in reverse genetic approaches or as in vitro models of human diseases. It is also a source of unique DNA fingerprinting information. Even though the process is time-consuming and expensive, it may be potentially utilized to pre-authorize the user to the highly secure facility along with other factors.
Subsequently, a comparison of the main indicators for the already deployed and emerging factors is given in Table 1. The factors/sensors are evaluated based on the following parameters:

Table 1. Comparison of suitable factors for MFA: H – high; M – medium; L – low; n/a – unavailable.

Factor Universality Uniqueness Collectability Performance Acceptability Spoofing
Password n/a L H H H H
Token n/a M H H H H
Voice M L M L H H
Facial H L M L H M
Ocular-based H H M M L H
Fingerprint M H M H M H
Hand geometry M M M M M M
Location n/a L M H M H
Vein M M M M M M
Thermal image H H L M H H
Behavior H H L L L L
Beam-forming n/a M L L L H
OCS n/a L L L L M
ECG L H L M M L
EEG L H L M L L
DNA H H L H L L

  • Universality stands for the presence of factor in each person;
  • Uniqueness indicates how well the factor differentiates one person from another;
  • Collectability measures how easy it is to acquire data for processing;
  • Performance indicates the achievable accuracy, speed, and robustness;
  • Acceptability stands for the degree of acceptance of the technology by people in their daily life;
  • Spoofing indicates the level of difficulty to capture and spoof the sample.
However, many other issues are to be addressed while integrating the MFA for the end users. In the following section, we elaborate on those challenges and formalize the recommendations for improved ease of integration.