Search results
Results from the WOW.Com Content Network
To serve its intended purposes, a fingerprinting algorithm must be able to capture the identity of a file with virtual certainty. In other words, the probability of a collision — two files yielding the same fingerprint — must be negligible, compared to the probability of other unavoidable causes of fatal errors (such as the system being destroyed by war or by a meteorite): say, 10 −20 or ...
Automated fingerprint verification is a closely related technique used in applications such as attendance and access control systems. On a technical level, verification systems verify a claimed identity (a user might claim to be John by presenting his PIN or ID card and verify his identity using his fingerprint), whereas identification systems ...
To match a print, a fingerprint technician scans in the print in question, and computer algorithms are utilized to mark all minutia points, cores, and deltas detected on the print. In some systems, the technician is allowed to perform a review of the points that the software has detected, and submits the feature set to a one-to-many (1:N) search.
A device fingerprint or machine fingerprint is information collected about the software and hardware of a remote computing device for the purpose of identification. The information is usually assimilated into a brief identifier using a fingerprinting algorithm .
A security tool can alert to potential fingerprinting: it can match another machine as having a fingerprinter configuration by detecting its fingerprint. [3] Disallowing TCP/IP fingerprinting provides protection from vulnerability scanners looking to target machines running a certain operating system. Fingerprinting facilitates attacks.
Fingerprint Cards is a Swedish biometrics company that develops and produces biometric systems. Fingerprint Cards was founded in 1997 by Lennart Carlson. Their products consist of fingerprint sensors, algorithms, packaging technologies and software for biometric recognition. [2]
Private biometrics is a form of encrypted biometrics, also called privacy-preserving biometric authentication methods, in which the biometric payload is a one-way, homomorphically encrypted feature vector that is 0.05% the size of the original biometric template and can be searched with full accuracy, speed and privacy.
A simulation of Kenneth Okereafor's biometric liveness detection algorithm using a 3D multi-biometric framework consisting of 15 liveness parameters from facial print, finger print and iris pattern traits resulted in a system efficiency of the 99.2% over a cardinality of 125 distinct randomization combinations.