Computational workload in biometric identification systems: an overview <s> Real-World Systems <s> The principle that underlies the recognition of persons by their iris patterns is the failure of a test of statistical independence on texture phase structure as encoded by multiscale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 249 degrees of freedom and generates a discrimination entropy of about 3.2 bits/mm/sup 2/ over the iris, enabling real-time decisions about personal identity with extremely high confidence. Algorithms first described by the author in 1993 have now been tested in several independent field trials and are becoming widely licensed. This presentation reviews how the algorithms work and presents the results of 9.1 million comparisons among different eye images acquired in trials in Britain, the USA, Korea, and Japan. <s> BIB001 </s> Computational workload in biometric identification systems: an overview <s> Real-World Systems <s> For the past three years, the United Arab Emirates (UAE) has employed an iris recognition system for all passengers arriving in the UAE by land, sea or air. By looking at an iris camera for a second or two while passing through immigration control, each passenger's iris patterns are encoded mathematically and the resulting image is sent over a distributed communications network to a central database where they are compared with the images from 420,000 people who were expelled from the UAE for various violations. Less than one second is required for each image to be compared against the full database. More than 9,500 people have been caught traveling with forged identities by this system. This article describes the system in detail, including the critical features of the system architecture and the algorithm for encoding and comparing iris patterns. The system operates in an "all against all" identification search mode. The decision thresholds are automatically adjusted according to the size of the enrolled database and thus the number of comparisons performed, so that there is no net accumulation of probability of false matches. This makes the system extremely efficient and accurate. All of the matches made so far between arriving passengers and violators in the database have been confirmed by other records. <s> BIB002 </s> Computational workload in biometric identification systems: an overview <s> Real-World Systems <s> This article discusses the implementation of iris recognition in improving the security of border control systems in the United Arab Emirates. The article explains the significance of the implemented solution and the advantages the government has gained to-date. The UAE deployment of iris recognition technology is currently the largest in the world, both in terms of number of Iris records enrolled (more than 840,751) and number of iris comparisons performed daily 6,225,761,155 (6.2 billion) in 'all-against-all' search mode. <s> BIB003 </s> Computational workload in biometric identification systems: an overview <s> Real-World Systems <s> Aadhaar is the world’s largest biometric database with a billion records, being compiled as an identity platform to deliver social services to residents of India. Aadhaar processes streams of biometric data as residents are enrolled and updated. Besides \(\sim \)1 million enrollments and updates per day, up to 100 million daily biometric authentications are expected during delivery of various public services. These form critical Big Data applications, with large volumes and high velocity of data. Here, we propose a stream processing workload, based on the Aadhaar enrollment and Authentication applications, as a Big Data benchmark for distributed stream processing systems. We describe the application composition, and characterize their task latencies and selectivity, and data rate and size distributions, based on real observations. We also validate this benchmark on Apache Storm using synthetic streams and simulated application logic. This paper offers a unique glimpse into an operational national identity infrastructure, and proposes a benchmark for “fast data” platforms to support such eGovernance applications. <s> BIB004 </s> Computational workload in biometric identification systems: an overview <s> Real-World Systems <s> The historical NEXUS iris kiosks log dataset collected by the Canada Border Services Agency from 2003 to 2014 has become the focus of scientific attention due to its involvement in the iris ageing debate between the National Institute of Standard and Technology and the University of Notre Dame researchers. To facilitate this debate, this study provides additional details on how this dataset was collected, its various properties and irregularities, and presents new results related to the effect of ageing, age, and other factors on the system performance obtained using the portions of the dataset that have not been previously analysed. In doing that, the importance of conducting subject-based performance analysis, as opposed to the traditionally done transaction-based analysis, is emphasised. The significance of factor effects is examined. Recommendations on further improvement of the technology are made. <s> BIB005
Due to confidentiality constraints (i.e. company or state secrets), the availability of details for real-world systems is not nearly as abundant as that of scientific publications. Nevertheless, this subsection will give several examples, based on the existing literature and personal communications. Aadhaar As of this writing, the Indian National ID Programme (see e.g.  BIB004 ) encompasses acquisition and usage of the largest biometric system in the world in terms of number of the enrolled data subjects. During enrolment, a de-duplication check must be carried out, in order to avoid issuing multiple unique identification numbers to the same individual. The de-duplication proceeds in several steps: first, obvious duplicates are pre-filtered out based on metadata (demographic information), either through exact matches or fuzzy matches followed by a preemptive biometric check. Subsequently, an exhaustive search of the biometric database is performed by one of the COTS systems provided by three different vendors. Each system uses a different implementation and information fusion (data from two irides and ten fingerprints is used) strategies. Any potential duplicate is verified by another system, and if the need arises, it is also adjudicated manually by a trained biometric system operator. The whole system design is distributed and massively parallelisable, and claimed to be scalable through use of commodity hardware and enterprise Big Data solutions. UAE The border control system in United Arab Emirates (see e.g. BIB003 BIB002 ) takes advantage of the intrinsically efficient iris representation (Iris-Codes, see BIB001 ) and distributed architecture of COTS components for quick biometric identification queries. It is reported, that an exhaustive search against the database of close to 1 million subjects can be executed within a couple seconds. I/O latency issues are avoided by pre-loading the entire enrolment database into random access memory. NEXUS In Canada, automated self-service kiosks for selected airports and (frequent) travellers are offered in order to expedite the border control process. The system uses iris as the biometric characteristic, and performs 1-to-first searches on the database of over 0.5 million enrolled data subjects for each biometric identification (see e.g. BIB005 ). EES Due to the specifics of the legal mandate  , the biometric systems for the EU visa and entry-exit system will be forced to perform exhaustive database searches. Due to the operational scenarios (such as border control), stringent requirements for quick (real-time) query responses have been imposed on the potential biometric systems vendors. It can therefore be expected that efficient data representations, information fusion schemes, as well as parallel/distributed design will be essential components of the forthcoming infrastructure solutions. AFIS Deployments of the Automated Fingerprint Identification Systems (see e.g.    ) are ubiquitous around the world and used for instance in the context of criminal investigations. Such systems are known to utilise computational workload reduction methods based on demographics, coarse fingerprint data (such as fingerprint type), along with highly optimised software algorithms to facilitate fast response times. Prominent examples include the Integrated AFIS (IAFIS) ran by the Federal Bureau of Investigation (FBI) in the USA and the database of the German Bundeskriminalamt (BKA). Industry In order to provide competitive search speeds for large biometric identification systems, commercial vendors of biometric recognition technologies, for example the German company Dermalog (information acquired through personal communication), are known to utilise methods of workload reduction in their products. National Institute of Standards and Technology (NIST) carried out an evaluation of 1:N face recognition vendors  . Among the details, it has been stated that several submitted algorithms take the expense of constructing fast search data-structures at enrolment, in order to achieve sub-linear search duration growth (with respect to the size of the biometric reference database). From the above examples, it is clear that computational workload is a critical consideration in operational systems and certain methods used to expedite the high number of queries handled by the existing large-scale systems around the world. To summarise in the context of the proposed taxonomy (recall figure 2), the following methods are represented in the list above: • Pre-filtering by metadata (e.g. demographic and geographic). • Search strategies (e.g. 1-to-first search). • Binning with coarse features (e.g. fingerprint types). • Intrinsically efficient feature representations (e.g. IrisCodes). • Software optimisation. • Massive parallelisation and distribution of computations. Notably absent are the methods of hardware acceleration (i.e. reconfigurable computing and graphical processing units) -it could be, that the practical matters (e.g. monetary implementation and maintenance costs) outweigh the benefits of potential speed improvements. Another potential important issue is vendor lock-in and the necessity of tailoring for specific software/hardware combination, which was deliberately avoided in e.g. the UAE and Aadhaar systems by making the design decision to use commodity CPUbased hardware (see e.g.  BIB003 ). The pre-selection methods, which are heavily researched, seem to be seldom used in those deployments. In other words, in this case there does appear to be (or perhaps is perpetuated by the information scarcity in this area), at least to a certain degree, a mismatch between what is researched in academia and what is actually used by the industry. This and other open issues are discussed in more detail in the next subsection.