BT/ Microsoft is expanding its speech biometrics offerings with the acquisition of Nuance

Paradigm

Follow

Published in

Paradigm

34 min readApr 26, 2021

--

Biometrics biweekly vol. 10, 12th April — 26th April

TL;DR

Microsoft is expanding its speech biometrics offerings for businesses and governments with the acquisition of Nuance Communications.
Keyless brings privacy-first biometrics to Microsoft, OneLogin, and Auth0 partnerships.
Careful criminals usually clean a scene, wiping away visible blood and fingerprints. However, prints made with trace amounts of blood, invisible to the naked eye, could remain. Dyes can detect these hidden prints, but the dyes don’t work well on certain surfaces. Now, researchers reporting in ACS Applied Materials & Interfaces have developed a fluorescent polymer that binds to blood in a fingerprint — without damaging any DNA also on the surface — to create high-contrast images.
A team of scientists from University College Dublin, Intel Ireland, and The University of Texas at San Antonio has improved biometric underage age estimation performance using an innovative method based on a regression-based model.
Researchers from the Michigan State University (MSU) are advocating the adoption of fingerprint biometrics for children of all age groups as part of efforts to tackle the problem of lack of official identification for children, which has often hampered the delivery of government services and access to medical care.
New research shows 3D printers can be identified by thermodynamic properties, which could aid intellectual property security.
Facebook wants to build trust in AI with its Casual Conversations dataset.
Oz Forensics passes iBeta biometric PAD test, BONAFiDEE launches liveness solution.
CLR Labs and LSTI partner on biometrics assessment for remote identity verification.
ID R&D expands support for face biometric liveness to Nvidia Jetson platform.
Global ID 3D vein biometrics patent filing published in Hong Kong.
Tascent multi-stage, multi-modal self biometrics enrollment patent could broaden iris recognition use.
Idemia is the latest digital identity provider to launch a Health Travel Pass, in the form of an app secured with facial recognition.
Apple analyst forecasts under-display face biometrics on 2023 iPhones.
Samsung deploys Suprema under-display fingerprint biometrics to Galaxy S21 series.
Spotify wants a dedicated spot on your car’s dash.
Draft EU rules would keep remote biometric identification under government thumb.
Atos builds edge facial recognition workplace safety system with Safr software.
BixeLab becomes first NIST-approved biometrics testing lab in Southern Hemisphere.
Buguroo rebrands as Revelock, launches behavioral biometrics platform and advisory board .
Open-source, Arduino-based wearable biometric sensor EmotiBit meets Kickstarter goal.
US digital ID regulation coming as feds seek info on mobile driver’s license standards.
Tascent gets device certification for biometric ID enrollment in Nigeria, unveils two new mobile SDKs.
BIO-key launches two new biometric fingerprint scanners for enhanced authentication security.
Iris ID, EyeLock ink new deals, Biosite launches contactless worksite entry solution.
Tackling the infant ID problem with fingerprint biometrics.
Biometric authentication with electrical muscle stimulation.
Biometrics for retail payments rolled out by Amazon, Sberbank, FPC.
SIA report: global increase in biometric border security and digital travel ID use.
Juniper predicts 1.4 billion software-based face biometric payments users by 2025.
Goode forecasts biometrics on 1 in 5 payment cards by 2026.
Biometrics Institute updates solutions review for COVID-19 recovery.
Biometrics industry events. And more!

Biometrics market

The Biometric system market size is projected to grow from USD 36.6 billion in 2020 to USD 68.6 billion by 2025; it is estimated to grow at a CAGR of 13.4% during the forecast period. Increasing use of biometrics in consumer electronic devices for authentication and identification purposes, the growing need for surveillance and security with the heightened threat of terrorist attacks, and the surging adoption of biometric technology in automotive applications are the major factor propelling the growth of the biometric system market.

Biometric Research & Development

Latest Researches:

Highly Stable, Nondestructive, and Simple Visualization of Latent Blood Fingerprints Based on Covalent Bonding Between the Fluorescent Conjugated Polymer and Proteins in Blood

by Zhinan Fan, Chi Zhang, Jiajun Chen, Rongliang Ma, Yaoqi Lu, Jia-Wei Wu, Li-Juan Fan in ACS Applied Materials & Interfaces

Careful criminals usually clean a scene, wiping away visible blood and fingerprints. However, prints made with trace amounts of blood, invisible to the naked eye, could remain. Dyes can detect these hidden prints, but the dyes don’t work well on certain surfaces. Now, researchers have developed a fluorescent polymer that binds to blood in a fingerprint — without damaging any DNA also on the surface — to create high-contrast images.

Fingerprints are critical pieces of forensic evidence because their whorls, loops and arches are unique to each person, and these patterns don’t change as people age. When violent crimes are committed, a culprit’s fingerprints inked in blood can be hard to see, especially if they tried to clean the scene. So, scientists usually use dyes to reveal this type of evidence, but some of them require complex techniques to develop the images, and busy backgrounds can complicate the analysis. In addition, some textured surfaces, such as wood, pose challenges for an identification. Fluorescent compounds can enhance the contrast between fingerprints and the surface on which they are deposited. However, to get a good and stable image, these molecules need to form strong bonds with molecules in the blood. So, Li-Juan Fan, Rongliang Ma and colleagues wanted to find a simple way to bind a fluorescent polymer to blood proteins so that they could detect clear fingerprints on many different surfaces.

The researchers modified a yellow-green fluorescent polymer they had previously developed by adding a second amino group, which allowed stable bonds to form between the polymer and blood serum albumin proteins. They dissolved the polymer and absorbed it into a cotton pad, which was placed on top of prints made with chicken blood on various surfaces, such as aluminum foil, multicolored plastic and painted wood. After a few minutes, they peeled off the pad, and then let it air-dry. All of the surfaces showed high contrast between the blood and background under blue-violet light and revealed details, including ridge endings, short ridges, whorls and sweat pores. These intricate patterns were distinguishable when the researchers contaminated the prints with mold and dust, and they lasted for at least 600 days in storage. In another set of experiments, a piece of human DNA remained intact after being mixed with the polymer, suggesting that any genetic material found after processing a print could still be analyzed to further identify a suspect, the researchers say.

Photos of blood fingerprints developed by three kinds of developing solutions with concentrations of 3.0×10–5 M, 3.0×10–4 M and 3.0×10–3 M (in repeat unit) on aluminum foil under natural light and 415 nm light.

ThermoTag: A Hidden ID of 3D Printers for Fingerprinting and Watermarking

by Yang Gao, Wei Wang, Yincheng Jin, Chi Zhou, Wenyao Xu, Zhanpeng Jin in IEEE Transactions on Information Forensics and Security

3D printing is transforming everything from fashion and health care to transportation and toys. But this rapidly evolving technology, also known as additive manufacturing, can threaten national security and intellectual property rights.

To reduce illicit use of 3D printers, Zhanpeng Jin, PhD, associate professor in the Department of Computer Science and Engineering at the University at Buffalo, is developing a way to track the origin of 3D-printed items.

His concern was that, as long as people have the digital design for an item, which can be downloaded from the internet, sometimes as open-source material, people can print out anything they want, which can range from computer parts and toys to fully functional handguns and assault rifles.

“So, what would be the best way to protect our intellectual property from someone else printing the same design using their own printer?” says Jin. “We wanted to find something internal. What would be the inherent signatures printed by my own 3D printer instead of another 3D printer?”

3D printers build three-dimensional objects by adding successive layers of printing materials according to the digital design for a 3D model. Each 3D printer has an “extruder,” which pushes the building material along. The extruder’s hot end then melts the material, and places it on the print bed to build the model.

In a paper, a research team led by Jin describes how each extruder’s hot end has its own unique heating properties, which impact the precise way that the 3D model is constructed.

Those thermodynamic properties can be used to identify the specific extruder and, thus, the model of 3D printer, as uniquely as a human fingerprint, or, as Jin calls it, a “ThermoTag.”

Jin compared the process to using a laptop to write a letter. Because software exists that can track keystrokes, an observer can see every step that went into the letter, including the writer’s unique writing style. Similarly, because of the unique properties of each 3D printer’s extruder, a researcher can examine the specific manner in which a 3D-printed object was made, and compare that to a database of various extruders until a match is made. From there, once the model printer is identified, the purchaser of said model can be tracked down if they had, say, used the printer to build an illegal assault rifle.

According to the research, Jin and his team discovered that, by examining and comparing the ThermoTag features of 45 different extruders of the same model, they were able to correctly identify the source printer with an accuracy rate of 92%.

“This ThermoTag will behave like the fingerprint of the 3D printer. When you print out a new product, you can use watermarking,” Jin says, noting that watermarking can be used to invisibly embed such information as the printer’s manufacturer, label and serial number in the product. “So that would make this watermark of this particular product unique.”
It’s possible, Jin says, that someone could replace their extruder to try to avoid detection. That’s why it’s important to create a database of these parts for comparison, he says.

Vec2UAge: Enhancing underage age estimation performance through facial embeddings

by Felix Anda, Edward Dixon, Elias Bou-Harb, Mark Scanlon, et al.

A team of scientists from University College Dublin, Intel Ireland, and The University of Texas at San Antonio has improved biometric underage age estimation performance using an innovative method based on a regression-based model.

Dubbed Vec2UAge, the model was trained from the VisAGe and Selfie-FV biometric datasets using FaceNet embeddings extracted and used as feature vectors. A third, unbiased dataset was then created to allow for balanced testing and validation. Generally speaking, age estimation models rely on age-labeled, good-quality images, but accurate age annotations in facial biometric datasets are often inadequate, according to the new research.

“Certain age groups have few samples — particularly the underage age range,” the report reads. “Datasets for this age range are difficult to find due to legal restrictions and ethical implications.”

Yoti is working on building its own database for age estimation biometrics in significant part to address this same problem. To circumvent this issue, the researchers chose the IMDB-WIKI and Adience datasets, respectively holding 500k and 26k age-categorized images.

During the experiment, the team also utilized various augmentation techniques to further expand the training dataset, then measured the deep neural networks’ learning rate (LR). For context, LR here refers to how much the system should change the model in response to the estimated error each time data sets are updated. A value too small may cause the training process to become too slow and eventually come to a halt, while a value too large may lead the system to an unstable training process or cause it to learn a sub-optimal set of weights too fast.

To find the optimal initial value for LR, the researchers then used a cyclic learning rate approach. They then evaluated the ensuing performance of the algorithms and concluded the new model achieved better performance than most algorithms today. The model reached a mean absolute error rate of 2.36 years.

“Current models usually attempt to tackle several challenging factors that affect the age estimation performance such as facial occlusion, non-frontal faces, brightness, contrast, quality, etc,” the report explains. “In our approach, a simpler challenge is addressed and a better performance is achieved.”

Moving forward, the team said it will continue to explore models to improve biometric age estimation performance, particularly through the use of a hyperparameter optimization framework for machine learning like Optuna.

Facial Image Augmentation Techniques: Original image taken from FG-NET Aging Database

Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection

by Ajian Liu, Chenxu Zhao, Zitong Yu, Jun Wan, Anyang Su, Xing Liu, Zichang Tan, Sergio Escalera, Junliang Xing, Yanyan Liang, Guodong Guo et al.

Face presentation attack detection (PAD) is essential to secure face recognition systems primarily from high-fidelity mask attacks. Most existing 3D mask PAD benchmarks suffer from several drawbacks: 1) a limited number of mask identities, types of sensors, and a total number of videos; 2) low-fidelity quality of facial masks. Basic deep models and remote photoplethysmography (rPPG) methods achieved acceptable performance on these benchmarks but still far from the needs of practical scenarios. To bridge the gap to real-world applications, researchers introduce a largescale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask). Specifically, a total amount of 54, 600 videos are recorded from 75 subjects with 225 realistic masks by 7 new kinds of sensors. Together with the dataset, they propose a novel Contrastive Context-aware Learning framework, namely CCL. CCL is a new training methodology for supervised PAD tasks, which is able to learn by leveraging rich contexts accurately (e.g., subjects, mask material and lighting) among pairs of live faces and high-fidelity mask attacks. Extensive experimental evaluations on HiFiMask and three additional 3D mask datasets demonstrate the effectiveness of the method.

TransRPPG: Remote Photoplethysmography Transformer for 3D Mask Face Presentation Attack Detection

by Zitong Yu, Xiaobai Li, Pichao Wang and Guoying Zhao, Senior Member in IEEE

3D mask face presentation attack detection (PAD) plays a vital role in securing face recognition systems from the emergent 3D mask attacks. Recently, remote photoplethysmography (rPPG) has been developed as an intrinsic liveness clue for 3D mask PAD without relying on the mask appearance. However, the rPPG features for 3D mask PAD are still needed expert knowledge to design manually, which limits its further progress in the deep learning and big data era. In this article, scientists propose a pure rPPG transformer (TransRPPG) framework for learning intrinsic liveness representation efficiently. At first, rPPG-based multi-scale spatial-temporal maps (MSTmap) are constructed from facial skin and background regions. Then the transformer fully mines the global relationship within MSTmaps for liveness representation, and gives a binary prediction for 3D mask detection. Comprehensive experiments are conducted on two benchmark datasets to demonstrate the efficacy of the TransRPPG on both intra- and cross-dataset testings. The TransRPPG is lightweight and efficient (with only 547K parameters and 763M FLOPs), which is promising for mobile-level applications.

Tackling the infant ID problem with fingerprint biometrics

A team of researchers from the Michigan State University (MSU) is advocating the adoption of fingerprint biometrics for children of all age groups as part of efforts to tackle the problem of lack of official identification for children, which has often hampered the delivery of government services and access to medical care.

According to an article by MSU Today, the research led by renowned biometrics expert Anil Jain, an MSU Distinguished Professor of computer science and engineering, began in 2014. Advances in the team’s work have come just ahead of increased attention around the world on vaccinations due to the pandemic.

After first developing a fingerprint system that worked well for toddlers one year and older, the team is now looking to extend the use of biometrics to include children of all ages with a high possibility of reducing suffering and deaths of children around the world.

One of the research team’s hallmark achievements is the development of a high-resolution child fingerprint reader which it designed alongside a specialized biometric matching algorithm. The device captured fingerprints of children at 1900ppi, which were still recognizable one year after, the article noted. The open-source high-resolution biometric scanner developed by Jain’s team can be built from widely-available components for around $80.

“My team of graduate and postdoctoral students have developed a system for digitally scanning an infant’s fingerprint that can be accurately recognized at least a year later. This system allows for accurate digital records, which is imperative to ensuring safety not only from the virus but other vaccine preventable diseases as well. Despite efforts of international health organizations and NGOs, children are still dying because it’s been believed that it wasn’t possible to use body traits such as fingerprints to identify children. We’ve just demonstrated that it is indeed possible,” the MSU article quoted Prof Jain as saying.

The research, conducted in India, has also been hailed by identity experts as a milestone in efforts to solve the problem of child identification, as highlighted by Dr. Joseph Atick, executive chairman of digital identity movement ID4Africa.

“The research of Jain and his team is unique in its rigor and in the promise that it embodies. Solving the infant ID problem through fingerprints will have profound consequences to the development agenda as a whole and to civil registration, child protection and health management, in particular. It will give today’s invisible children in the developing world a legal identity by tracing them to their origin, enabling them to assert their rights and to be fully included in society,” said Dr. Atick.

The test showed a 95 percent true acceptance rate after 3 months, 90 percent after six months, and 85 percent after 12 months for infants enrolled at 2 to 3 months of age, and a false acceptance rate set at 0.1 percent.

Young Frankensteins: Biometric authentication with electrical muscle stimulation

University of Chicago researchers have come up with the most improbable (so far) biometric method of authenticating someone’s identity — how fingers react to electrical currents stimulating forearm muscles.

The product, ElectricAuth, requires users to wear a sleeve embedded with electrodes. Electrical signals lasting about a second are sent in different numbers of pulses and at different tempos.

Nodes on their finger record the unique responses. The university researchers are working on a visual recording technique, and a press release announcing the idea shows people wearing augmented reality goggles that have a camera.

The school claims the setup provides 64 million potential interpretations for use in authenticating someone.

Main Development News:

Microsoft buys Nuance for $19.7B, expands voice biometrics footprint

Microsoft is expanding its speech biometrics offerings for businesses and governments with the acquisition of Nuance Communications. Microsoft, which first proposed the deal in December 2020, will acquire Nuance at $56 per share, 23 percent over Nuance’s latest stock closing value at $45.58 per share.

The deal would furthermore boost the speech recognition firm’s value to approximately $19.7 billion, making Nuance the second-largest acquisition after Microsoft’s 2016 purchase of LinkedIn for $27 billion. This milestone would follow Nuance’s recent global partnerships to provide its voice biometrics solution to call centers across various industries such as banking.

In 2020, Nuance reportedly recorded a net income of $7 million on approximately $346 million in revenue in the fourth quarter. The company, which is headquartered in Massachusetts, has grown since 1992 and as of September 2020 counts 7,100 employees. In 2019, Nuance and Microsoft partnered up to provide AI-driven voice biometrics for healthcare applications to improve the doctor-patient experience.

This latest addition expands Microsoft’s business and government-focused services. While Microsoft already offers developer tools to integrate speech recognition, buying Nuance greatly increases the company’s speech recognition capabilities.

Apple exploring mobile digital ID and wearable authentication tech

Two new patent filings signal that Apple is venturing into mobile device-embedded digital ID as well as wearable devices that include biometric sensors and motion-tracking for instant user authentication.

Patent application hints digital ID, ePassport, and mDL for iPhones/mobile devices

According to a new patent application, Apple might be exploring mobile user authentication for digital ID, mobile driver’s license (mDL), and ePassports. The specifications include the implementation of such a solution on Apple’s iPhone, allowing the mobile device to authenticate individual users in various scenarios such as age verification or travel.

The application explains, “Various governments are now issuing various forms of identification that are capable of storing identification information that can be used to authenticate a user. For example, modern passports (called e-Passports) may include an electronic chip that stores a passport holder’s name, date of birth, and other forms of information. When a person is passing through customs, the person may present the passport to a customs officer, who places the passport on a reader to extract information stored in the passport. Upon verifying the information printed on the passport against the internally stored information, the officer may confirm the identity of the holder and allow the holder passage through customs.”

The system in question would include a secure element, an NFC interface, a biosensor, a verification system, an authentication system, and an RFID tag for the ID document.

It further adds, “The present disclosure describes embodiments in which a person may present identification information through a mobile device instead of presenting a traditional form of identification. The present disclosure begins with a discussion about storing identification information (e.g., of a passport, driver license, government-issued ID, student ID, etc.) on a mobile device with respect to FIGS. 1–5B. The present disclosure then describes an authentication framework for performing a user authentication at the mobile device with respect to FIGS. 6 and 7.”

Apple continuation patent signals authenticated device assisted user authentication

A continuation patent signals Apple’s exploration of a system for authenticated device-assisted user authentication. The device might be worn in the form of a headband that would allow users to authenticate themselves instantly through their proximity to a device such as an Apple Watch, iPhone, or iMac that would require user authentication.

The application describes, “A system for user authentication includes an authenticated device with a restricted-access function that a user is able to access in response to verification of an identity of the user by the authenticated device and a proximate device with a restricted-access function that the user is able to access in response to the proximate device receiving authentication data that includes the identity of the user from the authenticated device. The authenticated device is operable to identify an absence of intent of the user to access the restricted-access function of the proximate device, and in response to identifying the absence of intent to access the restricted-access function of the proximate device, emit a locking signal such that, in response to detecting the locking signal, the proximate device enters a locked state and the restricted-access function of the proximate device is inaccessible to the user.”

The drawings detail a three-step authentication process that includes detection of the proximate device, determination of intent, and assisted authentication. The device might include one or more biometric sensors that would be used to confirm a user’s identity. User intent would be measured through motion-gesture tracking by the device.

Facebook wants to build trust in AI with its Casual Conversations dataset

Taking an active rather than reactive position on building trustworthy AI, Facebook has opened a new dataset to algorithm developers globally.

Casual Conversations is a collection of 45,000 videos of people chatting. The subjects are of various ages and skin tones and three gender choices. Lighting conditions also vary markedly. The dataset, something that is reused from a Facebook deepfake research project, is intended to be a reality check for developers who want to root out age, race and gender bias from their computer vision and/or audio products. Including voices is expected to help minimize biases based in audio applications, too.

It comes at a time when democratically elected governments and an increasing number of large businesses are trying to figure out how best to win over popular opinion about a topic that causes most eyes to glaze over in the details. Other eyes open wide with concern that AI will be used in unethical or dangerous ways.

Too often, proponents and vendors give lip service to the most important factor in AI’s future — its trustworthiness.

Facebook, the company and app that people love to hate to use every available moment, perhaps knows intimately that trust in technology that touches people’s personal lives cannot be taken for granted.

Everyone — all 3,011 people — talking in Casual Conversations were asked their age and gender rather than have researchers or software guess. That certainty makes the dataset considerably valuable to developers.

For gender, they could only choose male, female or other, something that Facebook almost apologizes for. The company explicitly points out it knows that that is “insufficient.” The dataset is a “good, bold first step forward,” and will be expanded over time to include other gender identities.

The company said it believes Casual Conversations is unique in that it is open sourced, includes paid actors who chose to participate and gets the gender and age information from participants.

Apparent skin tone for each participant was assigned by trained annotators, according to Facebook, based on the Fitzpatrick classification tool. The variable ambient lighting was tagged as well, to measure how skin tones look under less-clinical conditions.

Global ID 3D vein biometrics patent filing published in Hong Kong

Global ID is touting the privacy protection of authentication with its 3D vein biometric solution, and has also had a filing of its technology acknowledged by Hong Kong’s patent office.

The Intellectual Property Department of the Government of the Hong Kong Special Administrative Region included acknowledgement of Global ID’s ‘method and device for biometric vascular recognition and/or identification’ (see page 249) in its latest update.

The 3D vein biometrics technology was patented by the World Intellectual Property Organization (WIPO) in 2019, giving it protection in 153 countries under the Patent Cooperation Treaty, and Global ID filed for a U.S. patent last year. The company says that with recognition in Europe, the U.S. and now Hong Kong, it has filed applications in each of its three target markets. The 3D vein recognition patent application is one of nine filed by the biometric startup.

Global ID’s 3D vein biometrics technology is used in its BioID solution.

Global ID has also written a position paper on the protection of personal identity and privacy with ethical biometric authentication.

Biometrics provide the assurance that people are who they claim to be which is necessary to underpin online interactions, Global ID points out. The technology also poses risks if a biometric used to secure a person’s identity can be used by someone else without their permission, however.

“For obvious reasons of privacy and identity protection, biometrics must use a physical feature that is not continuously dispersed and replicated, such as fingerprints, DNA, and face, which are fine for criminal investigations but are not ethical for everyday use,” the company writes. “Consumers and citizen must be able to exercise control on when their biometrics are captured.”

Atos builds edge facial recognition workplace safety system with Safr software

Atos, a global provider of cloud, security and compute solutions, revealed it is using biometric technology from Safr, a division of RealNetworks, as part of a system for worker safety that integrates facial recognition software, cameras, and edge computing.

Paris, France-based Atos released a video, timed for the Hannover Messe trade show for industry and digital transformation, describing new offerings for workplace safety. The solution combines Safr’s facial recognition software with Atos’ BullSequanna Edge hardware. The new edge server includes two Nvidia T4 GPUs to help handle computer vision and data analytics processing.

Worker safety and computer vision applications have, over the course of the pandemic, tended to focus on actions such as fever detection, distance monitoring and mask detection. Atos’ solution takes facial recognition in a different direction. The firm noted that 20 percent of occupational accidents in 2019 (as reported in Germany) were caused by working with machines.

Atos describes two initial uses for the worker safety solution. The first involves machinery such as forklifts which are supposed to be operated only by qualified personnel. The Safr component performs the facial recognition functions to verify identity, while Atos hardware and software are used to allow access to machinery controls only after biometric identification occurs. In short, the employee’s face is the key to the forklift. The second related use case is using the edge server to track the user and machine around a facility and to geofence access to hazardous areas. If, for example, cameras identify a person in the vicinity of the forklift, the edge server can prevent the machine from moving (and hitting a human).

BixeLab becomes first NIST-approved biometrics testing lab in Southern Hemisphere

BixeLab is now fully accredited to perform independent third-party testing and reporting for biometric systems by the U.S. National Institute of Standards and Technology (NIST).

There are only two labs in the world accredited by NIST for biometrics testing, BixeLab and iBeta. iBeta Biometrics Project Manager Gail Audette discussed the benefits of the certification and what is involved with receiving and maintaining it earlier this year.

The certification allows BixeLab to introduce new capabilities and services to the market, and provide a standardized setting for biometric identity verification and identity software application testing, and compliance testing to laboratory and biometric standards from NIST and ISO/IEC.

BixeLab Managing Director Dr. Ted Dunstone writes in a LinkedIn announcement that the lab will support the accreditation of technologies and services for identity frameworks like Australia’s Trusted Digital Identity Framework (TDIF) or Singapore’s National Digital Identity (NDI), SingPass. The lab also has capabilities for evaluating other AI systems, according to Dunstone.

The company announced its intention to seek NIST accreditation earlier this year, and in a launch event presented its range of biometrics testing services. Those include performance testing to ISO/IEC 19795 and presentation attack detection (PAD) testing to the ISO/IEC 30107–3 standard, as well as for OCR accuracy, acquisition devices and biometric mobile apps, and evaluation of all common biometric modalities.

Buguroo rebrands as Revelock, launches behavioral biometrics platform and advisory board

Buguroo is now known as Revelock, in a rebranding by the company announced along with a new advisory board and a new platform for fraud detection and response, utilizing its behavioral biometrics and hybrid AI for continuous know your user, or ‘KYU’ verification.

The new Revelock Fraud Detection & Response (FDR) Platform provides all-in-one protection for web and mobile banking apps, the company says, with enhanced response capabilities delivered by bugFraud, which it characterizes as its previous flagship product.

The platform combines behavioral biometrics, network and device assessment with its hybrid AI to build a ‘BionicID’ digital fingerprint for the user. This is the KYU users are continuously verified against, and Revelock’s user models, population-based models and bad actor models are continuously updated to boost organizations’ ability to accurately detect bad actors and protect legitimate users without adding friction to the customer journey.

Revelock provides active defense, with full control over client-side automated risk mitigation for fraud analysts consisting of a Malware Blocker, Phishing Blocker and mRAT Blocker, as well as pre-emptive defense, which is comprised of Revelock Hunter (previously known as Fraudster Hunter) and the new Revelock Mule Disruption Services.

Tascent multi-stage, multi-modal self biometrics enrollment patent could broaden iris recognition use

Tascent has been awarded a new patent from the U.S. Patent and Trademark Office for a multimodal biometrics innovation which would bind a facial image enrolled through a selfie with an iris biometric image captured from the same person at a later time.

‘Binding of selfie face image to iris images for biometric identity enrollment’ describes a system Tascent says solves one of iris biometrics’ main implementation challenges, which is how to carry out staged enrollment to create a single identity record. The two biometrics are combined algorithmically in the proposed system.

Tascent points out in the patent that high-resolution imaging is now widely available to consumers in some markets.

“Self-pre-enrollment is a process used in a wide range of scenarios such as building physical access control, voter registration, personal banking, expedited travel and immigration, etc.” the inventors write. “However, these self-captured face images (herein referred to as “selfie” face images) are typically of variable biometric quality (for example, may be impacted by shadows, poor orientation, sub-optimal camera positioning, and/or confusing backgrounds). This impacts an accuracy of biometric systems that might make use of selfie face images, and limits their value.”

The need for dedicated and specialized enrollment devices has limited the adoption of iris biometrics so far, Tascent claims, prompting the company to look into a way to address this issue while tapping into the momentum behind smartphone-based enrollment apps.

Oz Forensics passes iBeta biometric PAD test, BONAFiDEE launches liveness solution

Oz Forensics recently announced its biometric platform has passed testing for compliance to the ISO 30107 Level 1 presentation attack detection (PAD) standard by iBeta Quality Assurance.

The algorithm underwent 300 original Liveness tests that were performed with real faces, with a false positive error rate of 1 percent. All 1,000 attempted biometric spoof attacks were detected by the Oz Forensics’ technology, according to the announcement.

Oz Forensics’ biometric platform is designed particularly to prevent biometric spoofing and deepfake attacks using Liveness detection.

According to the company, the Oz Liveness algorithm does not require individuals to look directly into the camera for identification and has processing speeds of up to one second.

“Oz Liveness AI algorithms check shots from the video and track dozens of parameters, [including] presence of glare and reflections, micromotions, pulse, etc,” explained the company’s CEO, Artem Gerasimov.
“We trained the system on tens of thousands of attacks. We work closely with 3D mask manufacturers and are constantly looking for new samples and challenges,” he added.

The iBeta biometric testing laboratory is accredited by the National Institute of Standards and Technology (NIST) under the National Voluntary Laboratory Accreditation Program (NVLAP).

iBeta was the first laboratory accredited by the FIDO Alliance under the FIDO Alliance Biometric Component Certification Program.

BONAFiDEE unveils new liveness test tool

UK-based regulatory technology firm BONAFiDEE has released a liveness test tool to strengthen its Visual Biometric Verification check.

Visual Biometric Verification allows for comparison between a real-time image and an ID document to verify the identity of an individual.

The new update introduces the capability to record a short video, quote a unique phrase within a limited time period, to prove that the user is ‘present’ in front of the camera

“We believe that with the launch of our innovative ‘liveness test,’ we have been successful in creating a solution that protects both organizations and their customers against the emerging deepfake fraud vulnerability,” commented BONAFiDEE Founder, Francis Lang. “It strengthens BONAFiDEE’s already robust identification process, bringing your customer one step closer”.

Biometric experts discuss presentation attack instruments

A recent discussion of biometric presentation attack instruments by Dr. Ted Dunstone and Stewart Pope in a session organized by BixeLab has been made available on YouTube.

The experts defined presentation attacks and described different standards and frameworks for biometric solutions to be able to effectively perform Presentation Attack Detection (PAD).

In particular, Dunstone and Pope explore the ISO/IEC 30107 standard, and how the document broadly defines the scope and requirements of PAD tools.

Tascent gets device certification for biometric ID enrollment in Nigeria, unveils two new mobile SDKs

Tascent has released two software development kits (SDKs) — the Mobile Face and the Mobile Device SDKs — with the aim of simplifying the process of integrating biometric capture capabilities by system integrators and engineers.

This comes as the company also earned certification by Nigerian National Identity Management Commission (NIMC) for its Tascent MX device which has been recommended for use for biometric enrollment within the framework of the country’s digital identity program.

According to a statement by Tascent, the SDKs which are flexible and convenient for use, will enable organizations easily integrate the collection of face, fingerprint and iris biometrics with their own applications.

The company explained that the Tascent Mobile Face SDK provides an API and a ready-to-use UI flow for detection, acquisition, and auto-capture of faces on standard mobile platforms, including iOS and Android; and by integrating it with their own mobile application, end-customers can seamlessly make sure their users can register their own biometric information.

The Mobile Device SDK, it stated, enhances biometric performance and reduces user inconvenience by providing pre-capture quality checking, a guided face capture experience and an image auto-crop and de-rotate ability.

Some of Tascent’s mobile devices such as Tascent M1 and Tascent MX get their API support from Tascent Mobile Device SDK for biometric fingerprint and iris capture and UI flows for detection, acquisition, and auto-capture of those modalities on supported mobile platforms, the statement noted.

Biometrics Institute updates solutions review for COVID-19 recovery

With organizations around the world facing changed, but still critical questions about how to resume operations, biometrics suppliers have responded to the evolving health threat with new solutions, as reviewed in a new report from the Biometrics Institute.

The 28-page report is an update of a resource collected by the Biometrics Institute as the pandemic began to take shape in May, 2020, and is intended to generate discussion, rather than as an endorsement of any particular technology or product, the organization emphasizes. The original paper was downloaded nearly 5,000 times.

Biometix contributes insights on the role of standards in vaccine passport development, Dermalog considers the future roll of iris recognition as a contactless biometric modality, Idemia writes about restoring confidence in travel, and Innovatrics makes the case for passive liveness detection. Jenetric weighs in on the future of fingerprint readers, while Jumio suggests five ways to avoid AI bias in online identity verification, Laxton Group pitches a hygienic approach to elections technology, Tech5 explores innovations for biometrics-based vaccination proof, Thales discusses biometrics in sports, and Veridas examines COVID passes as tools for economic growth.

Brands Australia, FacePhi, Phonexia and WorldReach also submitted solutions.

“The numbers of people still downloading the first report indicates this is clearly an area where our network is still looking for answers,” observes Biometrics Institute Chief Executive Isabelle Moeller. “This collection of solutions reveals some of the great work going on behind the scenes to get economies back on their feet.”

Open-source, Arduino-based wearable biometric sensor EmotiBit meets Kickstarter goal

A new biometric, wearable sensor module based on Arduino is now available on Kickstarter.

Dubbed EmotiBit, the open-source device can detect emotional, physiological, and movement data via more than 16 biometric signals.

“Wear in any orientation, anywhere on the body, and start measuring biometric signals! Built-in slots make it easy to wear EmotiBit any way you want,” reads the Kickstarter page.

Since the data is 100 percent user-owned, it can be recorded directly to the built-in SD card, and viewed through a cross-platform visualizer available for Mac, PC, and Linux, and built on the OpenFrameworks creative-coding toolkit.

The visualizer also allows for data streaming and, being open-source, enables further customization of the platform.

“Packed with sensors in a wearable form-factor, EmotiBit is 100 percent customizable and hackable thanks to its open-source technology,” the company explained. “EmotiBit is fully compatible with the Adafruit Feather ecosystem and Arduino. Easily tweak it to do anything you want!”

From a technical standpoint, the EmotiBit wearable device packs in several sensors capable of measuring body functions.

These include a GSR/EDA sensor to read emotional, cognitive, and physiological data, a thermistor to read body temperature, and a PPG sensor to measure heart rate, respiration, and other health biometrics.

EmotiBit is now live on Kickstarter, with early bird pledges starting from $199 for the basic package, and all the way up to a $375 Early-bird ‘Rockin’ & Researchin’ Bundle’ that includes the device, a research-grade EmotiKit Addon, a factory calibrated Adafruit Feather, a 400mAh battery, and a high-speed MicroSD card.