Details

Autor(en) / Beteiligte

• Vora, Aarohi
• Paunwala, Chirag
• Paunwala, Mita

Titel

A Score Level Fuzzy Rule based Multi-Biometric Framework for enhancing security of cloud access scenario

Ist Teil von

• 2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), 2019, p.1-5

Ort / Verlag

IEEE

Erscheinungsjahr

2019

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• One of the major authentication threats arises at the access entrance point of the cloud which leads to the need of developing a reliable authentication framework. Multimodal authentication systems represent an emerging trend for cloud information security. Multi-modal Biometric Frameworks (MBF) utilize more than one biometric identifier to recognize a person. MBF are expected to be more reliable due to the presence of multiple independent pieces of biometric traits. The aim of these multibiometric systems is to achieve a high reliability to determine or verify person's identity. The motivation for using fuzzy logic is that it offers methods best suited to model the information that is inherently uncertain and ambiguous. This paper implements score level fusion based on fuzzy logic for developing Fuzzy Rule Based (FRB) MBF. The matching module integrates fuzzy logic methods for matching score fusion. This approach is tested on the fingerprint and face score database of 102 people obtained from NIST BSSR1 database. The experimental results exhibits that the proposed method is comparable with the existing recognizing methods. The proposed FRB MBF results in enhanced security by achieving GAR of 90.2% at FAR of 0.0029 and EER equal to 0.078.