In the digital world, ensuring accurate identity and subsequently verifying that identity, are critical steps toward preventing fraud and other digital missteps. While digital access has given us easy and rapid control of our digital identities and various accounts, it also opens attack vectors that bad actors can use to their advantage. Having a comprehensive system of security processes and solutions in place is the best way to ensure a solid security posture.
The process of biometric identification involves the matching of a live sample against a database of existing biometric templates to find a record of a particular individual. In doing so, the system confirms that person’s identity. An automated biometric identification system, or ABIS, can help with large-scale biometric search identification by performing one-to-many comparisons of an individual sample to samples in a database containing many biometric templates. Biometric identification is not the same as the one-to-one verification. Biometric identification confirms who a person is; while biometric verification confirms they really are indeed that person as identified.
Aware provides a complete family of offerings for biometric identification and verification for law enforcement and civil identity needs. The AwareABIS™ Automated Biometric Identification System (ABIS) supports fingerprint, facial, and iris recognition for large-scale biometric identification. AwareABIS leverages BioSP™ (Biometric Services Platform), Aware’s market-leading workflow and integration server to achieve unsurpassed configurability and ease of integration. AwareABIS supports the NIST-tested Nexa™ face, fingerprint, and iris matching algorithms, as well as fingerprint algorithms from third-party providers. AwareABIS is also fast, scalable and reliable using Astra™.
Aware Astra is an advanced cluster computing platform used for large-scale biometric identification and deduplication using fingerprint, facial, and iris recognition. Highly scalable, Astra performs one-to-many search or one-to-one match against large stores of biometric and other identity data.