Best match

Most recent

In most cases access to the domain will be available within one to two hours of purchase, however access to domains purchased after business hours will be available within the next business day. How this works. How payment plans work Rather than paying the ...

BiomeB.com

HugeDomains

Get the most recent info and news about Biomeb on HackerNoon, where 10k+ technologists publish stories for 4M+ monthly readers.

Biomeb

Mitigating identity attacks in DeFi through biometric-based Sybil resistance

Many key healthcare industry players like Samsung, Alcatraz, Bosch, Suprema, NEC, and UiPath have all invested in building new biometric technology in order to support the healthcare industry. Although we’re still seeing fresh use cases emerge in the field of biometrics, there’s certainly the potential to is delivered to patients in the future. revolutionize how healthcare Already in industries such as finance and transport, we’re seeing the role that biometrics can play in swiftly and accurately identifying individuals and verifying their credentials. Although to imagine a future where keys and passwords will no longer be needed seems fanciful, biometric passports with fingerprint, facial, and retina recognition may soon pave the way for vastly improved security across the board. (Image: ) Research and Markets As we can see from the chart above, biometric technology has the potential to grow into a $51 billion industry by 2027, but how will this impact the world of healthcare? Let’s explore how biometrics could hold the key for revolutionizing how healthcare professionals deliver effective, secure, and accurate treatments for patients: Accurate Identification Measures As biometric technology grows, we’ve seen more businesses utilize biometric fingerprint scanners as a means of identification–particularly in the case of smartphones and in order to gain access to workplaces. These use cases have built a greater level of familiarity among users, which has seen more fingerprint scanners used within hospitals, care homes, and hospices in order to confirm the identity of both patients and staff. This form of identification works by recording a patient’s fingerprint and linking it to their medical record to verify who they are and their personal requirements instantly. The benefits of biometric identification in healthcare are vast. Firstly, it can reduce the instances of fraud by individuals claiming to be another patient in order to gain access to medication illegally–an act that per year because of patients incorrectly being allocated free prescriptions. reportedly costs the UK’s NHS £256 million Secondly, biometrics can eliminate the risk of human error in sourcing a patient’s medical history. Because their records are biometrically attached to their fingerprint, or other scans, medical records are virtually linked to their biological readings. This means that medical professionals can instantly consult records and discover whether their patients are eligible for free prescriptions, or have any important conditions to consider. Protecting Patient Privacy Biometric technology also provides a virtually impenetrable layer of patient privacy for healthcare organizations. Because they knowingly provide their biometric data, patients can provide their details on an opt-in basis and will have the choice of which organizations can access their records and for what purposes. Furthermore, the biometric details of patients can be encrypted, meaning that cybercriminals would be unable to hack into databases to steal patient data. These biological levels of encryption mean that patient medical records can remain fully private, and only accessible when biometric details are provided. Although their medical records will be stored in the cloud, electronic health records would only become accessible when a fingerprint or retina scan is completed, or when authorized medical teams with their own biometric access,  need to view them. Improving the Quality of Healthcare The implementation of biometric data throughout the healthcare sector can also help to unify clinical data by eliminating the prospect of duplicating medical records. Biometrics can also help to improve the accuracy of clinical records whilst improving the quality of . information that professionals have access to In turn, this can limit the level of incorrect treatments provided for patients–paving the way for stronger provision and quality of across the board. healthcare We’re also likely to see biometrics improve the quality of training for healthcare professionals in the future. Particularly in the field of high-risk roles like that of a surgeon, is likely to provide unparalleled experiences for professionals, with the progress in training programs linked to biometric identification like retina scans. This would empower surgeons to practice tasks on a virtual patient as if they were in a real-world operating theater. immersive training Building Bridges in the Future Naturally, many healthcare professionals will greet the introduction of biometrics with a degree of concern–much like the introduction of many revolutionary innovations. The act of identifying patients and accessing their data from biologically unique traits will alter how information is stored and protected, which will be difficult for some caregivers to familiarize themselves with. However, it’s clear that in the future, technologies like artificial and augmented intelligence will help to bridge any existing gaps that could emerge when professionals shift to biometric data and permissions. Blending AI and biometrics paves the way for hybrid technology to not only recognize and identify specific patients, but to also based on supporting characteristics like their voice, general appearance, and behavior–instilling an even greater level of accuracy in identification whilst removing the potential for healthcare fraud in a more comprehensive manner. begin learning more about patients Although we may be some years away from such a comprehensive blend of patient care, we’re already seeing the implementation of biometric technology emerge within the healthcare industry. As for where this intuitive technology can take us in the future, the sky’s the limit.

The Biometric Revolution Will Change Our Approach To Healthcare

Systems for access control, identification, and authentication all make heavy use of biometric recognition methods. Because it uses distinctive biological characteristics of individuals, such as fingerprints, facial features, and iris scans, to give access or confirm identity, biometric recognition is regarded as a secure authentication method. Like any technology, biometric recognition techniques are not 100% reliable and occasionally fall short. The integrity of the system and the data it safeguards may be jeopardized by these failures, which can also result in major security risks. In this post, we'll talk about how security issues are affected when biometric identification systems go wrong, using examples from actual situations. Types of Biometric Recognition Failures Biometric recognition failures can be broadly categorized into two types: false acceptance and false rejection. False acceptance When someone is mistakenly identified by the system as an authorized user when they are not, it happens. This failure may arise for several reasons, such as bad or insufficient security mechanisms in the system. Unauthorized access to secure locations, information, and systems may result from a false acceptance failure. biometric data False Rejection This problem often arises when the system fails to identify a legitimate user and refuses them access. This kind of failure can happen for several reasons, including bad biometric data, changes in an individual's biometric data over time, or programming faults in the system. False rejection failures may prevent authorized users from accessing secure areas or systems, which may have a detrimental impact on productivity. Failures in Biometric Recognition Examples Let's examine a few instances of biometric recognition failures and how security concerns are impacted: False Acceptance in Facial Recognition Technology The American Civil Liberties Union (ACLU) tested Amazon's facial recognition software, Rekognition, in 2019 by comparing images of members of Congress to a database of 25,000 publicly available arrest photos. The findings revealed that were mistakenly listed by the system as having been detained for criminal activity. This incident showed that facial recognition technology could have high false positive rates, which could result in innocent people being mistakenly classified as criminals. 28 members of Congress False Rejection in Facial Recognition Systems The use of facial recognition technology in security, surveillance, and authentication systems has grown in popularity in recent years. Yet, a variety of factors can sometimes cause technology to malfunction. For example, a news report from 2020 said that the facial recognition system employed by the had a high false rejection rate, resulting in innocent people being mistakenly labeled as suspects. This failure emphasizes how crucial it is to verify facial recognition algorithms for accuracy and make sure they are not prejudiced against particular groups. Detroit Police Department False Acceptance in Voice Recognition Systems Numerous more applications, such as virtual assistants and banking systems, use voice recognition technologies. Technology, however, is not perfect and occasionally fails for a variety of reasons. For example, a news piece from 2017 detailed how a its voice recognition technology after it was discovered that the system could be tricked by a fraudster using a vocal recording of the account holder. The system featured a high percentage of fraudulent acceptances, which allowed someone else to access the account holder's money without authorization. UK bank was forced to halt False Rejection in Fingerprint Recognition Systems One of the most popular biometric verification techniques used in a variety of applications is fingerprint recognition. Nevertheless, the technology is not infallible and occasionally fails for several different reasons. For example, filthy or dry hands can degrade the fingerprint's quality and cause it to be mistakenly rejected. A Malaysian study in 2013 found why most people experience trouble using fingerprint recognition-based biometric technology. Due to dry skin, many people's fingerprints get easily rejected by the recognition system, which may lead to . identity verification failure False Acceptance in Signature Verification Systems Systems that use a person's signature to verify their identification are called systems. This technology is not impervious, though, and it occasionally fails for several different reasons. For example, a news story from 2018 detailed how a bank in India was required to compensate a customer whose account was compromised as a result of a false acceptance error in the bank's signature verification system. The system had authorized a fake signature, which allowed someone else to get access to the customer's account. signature verification False Rejection in Voice Recognition Systems Virtual assistants and authentication systems are only two examples of the many uses of voice recognition technology. Technology, however, occasionally fails for many reasons. A system, for example, had a significant false rejection rate in 2020, according to a news item, which resulted in authorized users losing access to their accounts. The reason for the failure was said to be a change in the customers' voices brought on by things like background noise and changes in their health. UK Bank's voice recognition False Acceptance in Iris Recognition Systems Iris identification technology verifies a person's identity by using distinctive patterns in their iris. Nevertheless, this technology is not infallible and occasionally fails for many different reasons same as we saw in the section. For example, in 2018, researchers from the University of Barcelona showed how to mislead iris recognition systems by making fake iris images that may fool the system into mistaking one individual for someone else. This failure demonstrated the possibility of spoofing attacks against iris recognition systems. facial recognition failure Conclusion Failures in biometric recognition can have significant security repercussions while verifying users, resulting in unauthorized access, data breaches, and other unfavorable outcomes. It is crucial to put strong security measures in place, test biometric identification systems often for precision and dependability, and deal with any biases or vulnerabilities that might exist in the technology. By doing this, we may contribute to ensuring that biometric identification stays a safe and dependable authentication technique.

The Impact of Biometric Recognition Failures on Security

The Advent of BioMechaGenics (BMG) Enhanced This is an illustrated science fiction story that was generated by a web app from my uploaded content. By 1980 the levels of greenhouse gases had climbed far higher than anything seen for many millions of years, and by the start of the 21st century, it was clear that there was a major connection between global temperature and greenhouse gas levels. Now the computer models, with wholly independent methods and data, were predicting processes that would bring rapid and severe global warming, a disruption of climate exceeding anything seen since the emergence of the human species. The models said the threshold for dangerous global warming would be crossed between 2027 and 2042. This was the milieu that would see the advent of . BioMechaGenics (BMG) Enhanced It was an incredible claim, yet the evidence was incontrovertible to the observant. Precariously perched balancing boulders, deeply scarred and abraded bedrock surfaces, deposits of moraine gravel; all very like the artifacts seen with glaciers, save for evidencing some stupendously enormous scale. By the late nineteenth century it was generally accepted that entire northern continents had once been covered with kilometers thick ice sheets, and that in fact our Stone Age ancestors had lived through one such epoch. Indeed, by the end of the nineteenth century it was determined that this ice age or period of extreme climate change had happened more than once over recent geologic time. The ice had advanced and receded repeatedly. Further discoveries soon indicated that this period of glaciation and climate oscillation was a relative anomaly that only occasionally punctuated much longer epochs of a stable and consistently warmer climate, periods that had left fossil evidence of tropical plants in now frigid areas. And yet causality was ever the crux. What could serve to explain these profound changes from a balmy warm to a glacial epoch, and then further the cycling of ice ages within a glacial epoch? No acceptable explanation was immediately obvious. Over the hundred years stretching between the mid nineteenth to the mid twentieth centuries a number of explanations were posited. For example Croll and later Milankovitch suggested that the periodic climate changes were attributable to subtle variations in Earth's orbit and inclination with resultant changes in sunlight on the northern hemisphere. It was a grand idea and improvements in our ability to determine the dates of these changes lent further credence to the astronomical theory. By the 1970's most scientists accepted that the Milankovitch cycles coincided precisely with the climate changes they saw evidenced before them. More difficult to understand was how these minor changes in sunlight and orbit could manifest such profound changes in climate. Based upon these cycles and their repetitions it was assumed that we were then on the cusp of a cooling spell. A new ice age was expected to be in advent over the next thousand years. Then by 1985 ice cores extracted by a French-Soviet team at Vostok Station in Antarctica contained an entire glacial epoch together with samples from before and after. Analysis of the entrapped gas content showed that the amount of atmospheric carbon dioxide coincided with the temperature variations. By 2012 this was of particular interest because the climate seemed to be warming, not cooling, and as time went on the warming changes became more evident. In addition, the amount of atmospheric carbon dioxide was far higher than it had been even in previous warm epochs extending back millions of years. The other significant greenhouse gas, methane, was present at higher levels than seen in any historic record. Meanwhile at the beginning of the twenty-first century feedback effects were beginning to kick in, feedbacks that were accelerating dramatic climate change. These warming changes were not prompted by variations in sunlight as had previous changes but instead were prompted by changes in atmospheric gas content, and predicting likelihoods was problematic. Still, it is certain that some government agencies and a few NGO's had anticipated the high probability of extreme climate and environmental changes along with catastrophic collateral socioeconomic impacts. To what extent their subsequent behaviors and actions were influenced by these assumptions is moot. What became clear to almost everyone during the third decade of the 2000's was that warmer and drier taken together were synergistically detrimental to human agriculture and human comfort. The widespread failure of what were formerly staple crops led to hunger and consequent conflict. Even so the powerful continued to maintain their dominion over resources and technologies while the worth of ordinary humans diminished. There were, after all, so very many of them, and beyond that there were more new arrivals every day. You couldn't even bomb enough of them back to the Stone Age to eliminate the species' continued proliferation. But where humans had failed to exterminate as many of their fellows as they had tried, perhaps the climate would succeed. While the interminable drought and incessant heat had limited the amount of available fresh water, rising sea levels were diminishing the available land. For better or for worse, both the temperature and the sea level were rising faster than had been anticipated. From orbit one could witness the steadily increasing inundation of the Earth below. BMG's founders referred to those circumstances, to that milieu, as the world BioMechaGenics had inherited. But there were some, dangerously wrong minded individuals, who maintained that BMG had contributed to creating the world as it had by then become. These recidivists could not, indeed would not, grasp the inexorable and inescapable nature of events as they unfolded. To be continued...

The Advent of BioMechaGenics (BMG) Enhanced

Biometric technology is becoming increasingly widespread around the world. The key driver of biometrics large-scale adoption is its integration into mobile devices. Today, many of us interact with some form of biometric authentication every day—this is how we unlock our phones, log into mobile banking apps, or authorise payments. The technology relies on biometric data to establish or verify a person’s identity. This involves scanning and mapping one’s physical traits, such as facial features, fingerprints, the retina, or the capillary pattern. All these biometric characteristics are generally unique to individuals, and therefore, are a reliable method of identification. The applications for biometric recognition are numerous, but in this article, I’ll specifically look into one—bio-acquiring, or biometrics-enabled payments. In this case, an individual’s bank account is linked to biometric data which is used to approve transactions, for example, paying for purchases. Both businesses and consumers worldwide have embraced the technology for it provides a secure and speedy way to verify identity, resulting in a seamless payment experience. Why Biometrics? One primary benefit of the technology is the fact that biometric data is always "with the consumer" and cannot be lost or forgotten. Yet, the value of biometric-authenticated transactions extends far beyond that. These are the three main reasons why more and more consumers rely on biometric data  when making payments: Biometrics eliminate the need to memorise multiple unique PIN codes and passwords. Ease of use: Short four-digit PINs or even more complex passwords don’t guarantee absolute security since they can be stolen or otherwise compromised. Biometric verification relies on a person’s unique physical features, which are extremely hard to replicate. Security: Although the difference might at first seem barely noticeable, biometric authentication is faster and more straightforward than entering a PIN or a password. This benefits both consumers and businesses, as the frictionless payment experience helps to increase conversion. Speed: China Currently, China is a clear leader when it comes to biometric payment adoption. The two main promoters of the technology are Alipay, owned by Alibaba Group, and its rival WeChat Pay, operated by Tencent Holdings. Alipay pioneered fingerprint scanning for payments way back in 2014, with WeChat Pay catching up merely a year later. In 2017, Chinese consumers saw the rollout of facial recognition payment technology. As of today, Alipay has facial recognition payment systems installed in over 100 cities across China. According to iiMedia Research Group estimates, in 2021 more than 495 million Chinese citizens used  face biometrics for payments, which roughly amounts to one third of the country’s population. Chinese banks have also been quick to pick up on the trend. ATM users at China’s four major banks can perform transactions by having their faces scanned. One example is China Construction Bank, which has equipped half of its ATM fleet with facial recognition technology. The key driver for biometric payment development in China is the national biometric ID. India In India, biometric identity schemes are helping to bring the unbanked into the financial system. One such initiative is the Aadhaar register, which contains the biometric data of more than one billion Indian citizens. Launched in 2009 as a way to streamline government welfare schemes and combat poverty, the Aadhaar program has since outgrown its original idea: in today’s India, even some of the most basic services, such as opening a bank account or purchasing a cellphone plan, require providing an Aadhaar number. The biometric data that Aadhaar holders submit includes fingerprints and iris scans. The majority of Aadhaar-mediated transactions are authenticated with fingerprint biometrics, which makes it the most commonly used payment method in India. The USA Amazon One, a contactless palm-print based payment service, was introduced by Amazon in its Amazon Go stores back in 2020, amidst the COVID-19 crisis. The device requires a user to hover their hand over a scanner and verifies identity based on such characteristics as vein patterns as well as lines and ridges on the palm surface. It then creates a unique palm signature for each user and associates it with their bank card number. In 2021, the technology made its way to third-party facilities as Whole Foods introduced the palm-print checkout system in its retail stores and AXS, a leading digital ticketing company, integrated Amazon One into its contactless ticketing panels at Red Rocks Amphitheatre in Denver and four Climate Pledge Arena venues in Seattle. To date, Amazon One is available in more than 70 Amazon retail stores, Whole Foods grocery stores, and a number of other partner stores. Embedded Biometrics Smart bank cards with a built-in fingerprint scanner date back as far as 2017, when Mastercard trialed the technology in South Africa. The card can verify its holder’s identity for in-store purchases through a combination of sensor and chip technologies. Once the sensor captures the fingerprint, this data is then matched to the digital template stored in the chip. To make a payment, one simply needs to hold their finger over a sensor instead of typing in a PIN code. In fact, fingerprint authentication is expected to fully replace PINs since sensor-enabled biometric cards can provide proof of life, which can be leveraged to help mitigate and combat social, welfare, and Card-Present (CP) fraud. Whether this claim actually holds true, only time will tell, yet the fact that  biometric sensor cards work with traditional payment terminals and require no investment into new Point of Sale (POS) infrastructure, can definitely stimulate their wider adoption. And the Rest of the World? Bio-acquiring is developing rapidly in other countries as well, prompted by COVID-19, which fast-tracked the global adoption of low-contact or contactless payment methods. One example is PopID, a Los Angeles-based company that promotes facial recognition for restaurant ordering and entry passes. In Europe, the Spanish CaixaBank and BBVA banks are the most active drivers of biometric payment technologies with proprietary solutions for restaurants and cafes. A face recognition-based payment system is also being tested in the Seoul metro, and the Israeli startup Preciate is implementing biometric retail payments in catering networks and stores.

How Biometrics Reshape Payments Worldwide

The travel industry, post-Covid, actually looks a lot brighter. Sure, it’s different. But it’s definitely brimming with promise all thanks to the travel tech that erupted out of the woodwork when everyone was trapped at home, unable to travel anywhere. Travel tech now encompasses not just the platforms that can help travelers get somewhere, be it planning an itinerary or having improved hospitality features that are safe, secure, and most importantly, low contact. In the midst of fending off Covid-19, we developed a taste for personal space and minimal contact. People are now opting for contactless parcel deliveries or food deliveries, and the same can be said for travel because now we have augmented reality, which will bring travel to a whole new level of social interaction without being physically present. Never Worry About Being Lost in Translation Again When Google rolled out its Google Translate service that gave people the option to scan signage or menus and (in real-time) to English, it was a game changer. have it translated Suddenly, language didn’t seem like that much of a barrier anymore and it will immerse travelers much more richly into the culture of the country they are visiting, which will help them experience travel like never before. This innovative creation has given rise to many different platforms that basically do the same thing. You have Microsoft Translator and Papago, each with a better handle on a different language. Take Papago for instance, it is better with Korean and other Asian languages than say Google Translate, which is much better at handling Hindi, Tagalog, and Indonesian, amongst other Euro-centric languages. It is similar to Onsego, in that it provides education for a specific purpose. Augmented Reality, Virtual Reality, or Metaverse One day, logistics will become a distant dream - or nightmare, depending on how you look at it - and you won’t have to worry about your airport transfer or whether you’ll have a boat to take you to an island you’re trying to visit in the middle of monsoon season. In fact, you won’t have to worry about the weather at all because while your mind is traveling, your body is staying put right where you wore your VR headset. When Mark Zuckerberg announced Metaverse, it was intended to bring the world closer together like never before. Anyone with a VR headset will be able to jump into a world of their choosing and interact with someone halfway across the world if they wanted to. But of course, there’ll still be people who like to be present, but that doesn’t mean that they can’t take virtual tours to try out different tours to see which one they prefer or when it comes to choosing a hotel. Will Robots Be Our Next Hosts? In the same vein of low contact or no contact at all during our travels, we might be served entirely by robots in the future. There will be no waitstaff for you to yell at because everyone will be ordering their own food digitally through their phones after scanning a QR code, and a robot will bring your food to you. Cook times will be nailed down to a second because robots will be manning the kitchen, with no room for human error. The same may happen in accommodation, with the implementation of baggage robots, housekeeping robots, and maybe even a concierge robot. There is even news of immigration robots that will scan passengers for weapons or other concealed and illegal items. The world would be much more mechanical and a lot safer with robots to create a more seamless and user-friendly experience in the real world. taking over roles Facial Recognition Technology May Render the World Visa-Free Just think about why we need visas. According to Passport Index, “Countries have visa restrictions in order to check and control the flow of visitors in and out of the country and to prevent illegal immigration and other criminal activities.” When all your personal records and information is tied to your face, there will be no need for any kind of third-party validation that tourists are simply in the country for pleasure, or that the working permit that someone is holding is fraudulent. Everything will be linked and uploaded, which will also bring about a higher level of security. Biometric Exit in America is already in order to curb illegal immigration. rolling out their services At the same time, biometrics and facial recognition technology may even make payments even more painless than it already is today, with all the e-wallet options available on the market. Just think, you may not even need to convert your currency into local pesos or yens anymore, your expenses will just be deducted automatically from your virtual accounts whenever you check out of a hotel or leave a restaurant.

Traveltech in 2023: Metaverse, Robots, and Biometrics

Workspace security can be a fiddly money drain, especially for corporations that deal with sensitive information or run multiple offices with thousands of employees. Electronic keys are one of the standard options for how security systems can be automated, but in reality, there are tons of downsides like lost, forgotten, or faked keys. Biometrics have shown solid alternatives to conventional security measures since they represent a concept of “what-you-are” authentication. This means a person can use their unique characteristics like fingerprint, iris, voice, or face to prove they have access to a certain space. Using biometrics as a method to authenticate guarantees the key can’t be lost, forgotten, or fabricated. So today we’ll speak about our experience with edge biometrics, which is the combination of edge devices, AI, and biometrics to implement AI security monitoring systems. What Are Edge Biometrics? First things first, what is ? In a traditional architecture of artificial intelligence, a common practice is to deploy models and data in the cloud, separate from the operating device or hardware sensor. This forces us to maintain the cloud server in a proper state, preserve a stable internet connection, and pay for the cloud service. If the storage appears inaccessible in case an internet connection is lost, the whole AI application becomes useless. edge AI “In contrast, the idea of edge AI is to deploy artificial intelligence applications right on the device, closer to the user. Edge devices may have their own GPU which allows us to process the input in place on the device. This provides a number of advantages such as reduced latency due to fact all actions are performed locally, on device. Overall cost and power consumption also become lower. Additionally, the system becomes portable, since the device can be easily moved from one location to another. Given the fact we don’t need large ecosystems, bandwidth requirements are also lower opposed to traditional security systems that rely on stable internet connection. Edge device can operate even in case of connection shut down, as data can be stored in device’s internal storage. Which makes the whole system design more reliable and robust.” Daniil Liadov Python engineer at MobiDev The only notable pitfall is that all the processing has to be done on the device in a short amount of time, and the hardware components need to be powerful enough and up to date for this function. For tasks like biometric authentication with face or voice recognition, fast response and reliability of the security system are critical. Since we want to ensure seamless user experience and proper security, relying on edge devices gives those benefits. Biometric information like employee faces and voices appears to be secure enough since they represent unique patterns that can be recognized by neural networks. Additionally, this type of data is easier to collect, as most businesses already have photos of their employees in their CRM or ERP. This way you can also avoid any privacy concerns by gathering, say, fingerprint samples of your people. Combined with edge, we can create a flexible AI security camera system for workspace entrance. So let’s discuss the implementation of such a system based on our own experience of automating office entrance processes with the help of edge biometrics. AI Surveillance System Design The main idea behind the project was to authenticate employees at the office entrance with just a glance in the camera. The computer vision model is able to identify a person’s face, compare it with the previously obtained photo and unlock the door. Voice verification was added as an additional step to avoid tricking the system in any way. The whole pipeline consists of 4 models that carry different tasks from face detection to speech recognition. All of these steps are done through a single-edge device that serves as a video/audio input sensor, as well as a controller for sending commands to lock/unlock doors. As an edge device, has been chosen. The main reasons behind this choice were the presence of GPU memory (which is vital for accelerating inference for deep learning projects) and the availability of Jetpack – SDK from NVIDIA, which allows coding on devices in Python3. Therefore, there is no strict need to convert the DS model to another format and nearly all of the codebase can be adapted to the device by DS engineers, so no rewriting from one programming language to another is required. NVIDIA Jetson Xavier So the general flow looks as follows: Input image is provided to the face detection model to find the user. Face identification model runs inference by extracting vectors and comparing them with the existing photo of an employee to identify whether it’s the same person. Another model is fed with voice samples to verify the voice of a specific person. Additionally, speech-to-text anti-spoofing is used as a technique to prevent any type of trickery. Let’s discuss each of the elements, and elaborate on the training and data collection procedure. DATASET GATHERING Before diving deep into system modules, it’s important to note what database is used. Our system relies on the availability of so-called reference, or ground-truth data for users. This data currently includes precomputed face and voice vectors for each user and looks like an array of numbers. The system also stores data from the successful attempts of logins for their possible use for re-training later. Given this, we’ve chosen the most lightweight solution, SQLite DB. With this DB, all the data is stored in a single file that’s easy to browse and back up, while data science engineers’ learning span is shorter. Since facial recognition requires photos of all employees that may enter the office, we used facial photos stored in corporate databases. A Jetson device placed on the office entrance also collected face data samples as people used face verification to open the door. Voice data wasn’t available initially, so we organized data gathering by asking people to record 20-second clips. Then, we used a voice verification model to obtain vectors for each person and stored them in DB. Voice samples can be collected with any audio input device. In our case, casual mobile phones and web cameras with inbuilt microphones were used to record voices. FACE DETECTION Face detection provides an answer to the question of whether there are any faces in a given scene. If there are, the model should give coordinates of each so you will know where each of the faces is located on the image, including facial landmarks. This info is important because we need to receive a face in a bounding box to run face identification on the next step. For face detection, we used the model with a MobileNet backbone from the InsightFace project. This model outputs four coordinates for each detected face on an image as well as 5 facial landmarks. The fact that images captured at different angles or with different optics can change the proportions of the face due to distortion. This may cause the model to struggle to identify the person. RetinaFace For this need, facial landmarks were used to perform warping, a technique to reduce possible differences between these images of the same person. As a result, obtained cropped and warped faces will look more similar, and extracted face vectors also will be more accurate. FACE IDENTIFICATION The next step is face identification. At this stage, the model has to identify the person from a given image, which is the obtained picture. Identification is done with the help of references (ground truth data). So here, the model will compare two vectors by measuring the distance score of the difference between two vectors to tell if it’s the same person standing before the camera. This assessment is compared with the initial photo of an employee we had. Face identification is done with the model with architecture. In order to make the model results more robust, before obtaining the face vector input, the image is averaged with the flipped version of itself. At this point, the flow of user identification looks as follows: SE-ResNet-50 VOICE VERIFICATION Next, we move to voice verification. This step should verify if two audios contain the voice of the same person or not. You may ask why not make allowance for voice identification as well? The answer is that facial recognition works much better than voice nowadays, and an image gives more information to recognize the user than a voice. To avoid identifying the same person as user A by face, and user B by voice, only face recognition is applied. The basic logic is almost the same as in the face identification stage, as we compared two vectors by the distance between them unless we found similar vectors. The only difference is that we already have a hypothesis about who is the person who is trying to pass from a previous face identification module. During the active development of the voice verification module, many issues were popping up. The previous model with Jasper architecture was not able to verify the recordings of the same person taken from different microphones. So we solved this problem by using architecture, which was trained on the dataset from the SpeechBrain framework which did a better job at verifying employees. ECAPA-TDNN VoxCeleb2 However, audio clips still needed some pre-processing. The goal was to improve the quality of audio recording by preserving voice and reducing present background noise. However, all the tested techniques affected the quality of the voice verification model badly. It is likely that even the slightest noise reduction could modify voice audio characteristics in recording so the model will not be able to correctly verify the person. Also, we performed an investigation into how long the audio recording should be and how many words the user should pronounce. As a result of this investigation, a few suggestions have been made. Such a recording should have a duration of at least 3 seconds and around 8 words need to be spoken. SPEECH-TO-TEXT ANTI-SPOOFING The final security grain was added with speech-to-text anti-spoofing built on from the Nemo framework. This model provides a decent quality user experience and is suitable for real-time scenarios. To measure how close what the person says to what the system expects, requires calculation of the Levenshtein distance between them. QuartzNet Obtaining a photo of an employee to trick the face verification module is an achievable task, as well as recording a voice sample. Speech-to-text anti-spoofing excludes scenarios in which an intruder tries to use a photo and audio of an authorized person to get inside the office. The idea is quite simple: when each person verifies themselves, they pronounce a phrase given by the system. The phrase consists of randomly selected words of a chosen set. While the number of words is not huge in a phrase, the actual number of possible combinations is. Applying random generation of phrases, we eliminate the possibility of spoofing the system, as it will require a large number of recorded phrases spoken by an authorized user. Having a photo of a user is not enough to trick an AI security system with this protection in place. The Benefits Of The Edge Biometrics System At this point, our edge biometric system follows a simple flow for a user, which requires them to p say a randomly generated phrase to unlock the door. Additionally, with face detection, we provide AI surveillance for the office entrance. “By adding multiple edge devices, the system can be scaled to different locations or easily modified. We can directly configure Jetson through the network, set up connection with low-level devices via GPIO interface, and upgrade it with new hardware quite easily, compared to a regular computer. We can also integrate with any digital security system that has a web API. But the main benefit here is that we can collect data for improving the system right from the device, since it appears convenient to gather data on the entrance, without any specific interruption.” Daniil Liadov Python engineer at MobiDev Written by , AI Engineer at Dmitriy Kisil MobiDev. The full article was originally published and is based on MobiDev technology research. here

Developing AI Security Systems With Edge Biometrics

Desarrollo de sistemas de seguridad de IA con Edge Biometrics

The metaverse Yet another sci-fi phenomenon in the tech world and the spaces of crypto, gaming, and art — the metaverse is the futuristic concept that refers to a persistent simulated online digital universe that mimics the real world. On the tech side, to provide an immersive experience for its users, the metaverse combines multiple elements, including such integral components as VR, AR, MR, and blockchain, along with social media concepts. Coined in the early 1990s by American science fiction writer Neal Stephenson in his novel , the term ‘metaverse’ originally described a virtual world in the imagined future where VR goggle-wearing users inhabit 3D avatars and buy and sell virtual real estate on a planet-encircling market. Snow Crash Today it is considered more as a future iteration of the internet that creates a shared 3D virtual space, an environment that enriches users’ interaction while they perform online the activities that they do in everyday life, whatever they are — working or shopping, playing games, or socializing together. The metaverse concept has been a buzzword and one of the hottest trends, especially after Facebook’s announcement that it was rebranding to Meta, and giant companies like Microsoft, Google, and Sony dived into the metaverse with their unique platforms or started investing. Currently, there are plenty of metaverses out there, for example, the popular virtual world Decentraland, the Pokemon-inspired play-to-earn metaverse game Axie Infinity, and the digital gaming platform The Sandbox. While a single, united metaverse with unified online infrastructure and real-time events is likely a way off, the developments that may lead to its creation are already here. Advantages of the metaverse The most notable one is that the metaverse , connecting the world and negating physical distance. It brings some kind of equality. The metaverse acts as a neutral space where everyone can meet as equals to some extent. destroys geographic barriers On top of that, the metaverse , mainly for business and educational institutions. With the benefits of 3D virtual worlds and engaging seamless experiences, social interactions and events are way more immersive. Keep in mind, that since the raging pandemic grasped the world in its clutches in 2020, individuals and organizations recognized the value of remote or distance interactive meetings, working, and learning in event of restrictions. So today it makes sense. has the potential to bring innovations in communication Another metaverse advantage . The metaverse economy can serve as the ideal platform for exchanges of digital assets with real economic value. Cryptocurrency and NFTs play crucial roles here through blockchain technology providing decentralization, transparency, and trust. Due to them, the metaverse provides the right grounds for innovative advancements in DeFi, GameFi, and tokenization of content. focuses on the creation of a separate virtual economy Also, the metaverse brings up beyond Web2, along with establishing its role in marketing. new opportunities for expanding branding and social media A late 2021 Statista survey of global internet users that overcoming obstacles that prevented them from doing something in real life was perceived as the biggest benefit of the metaverse. Enhancing creativity and imagination was ranked second with 37 percent of respondents claiming this as a benefit. The metaverse also holds promise for upskilling, education, and exploring new career opportunities. found Cons of the metaverse However, despite the apparent advantages, as always, there are two sides to every coin. It is difficult not to pay attention to and other sorts of illegal activities that are already disrupting the existing extremely vulnerable digital space. cyber security crime, fraud, Sybil attacks and identity theft , The statistics insane numbers — around 1 in 15 people become victims of identity fraud. And in 2022 identity theft scenarios are increasing drastically. There were 5.7 million reports of identity theft and fraud in the US only last year, up from 4.7 million in 2020. With a $500 median loss, the cost to victims is growing as society becomes more digitally dependent. show One of the reasons why security threats remain is that people store, contribute, and share a lot of personal information (PII) and sensitive data online. Events like the that exposed 700 million user records confirmes that, shaking the digitized world to the bone over and again. LinkedIn breach One of the most significant security risks in the digital space is the one that is associated with social networks. Users can never be 100% sure that you interact with the exact person they want to connect with — or with a real person altogether. In the metaverse, with the proliferation of avatars and lack of moderation, communication with the right individual may become even more challenging. In addition, in the metaverse where people will enter more networks via various tools like VR goggles, mobile devices, and various services, the risk of fraudulence or device thievery is much higher. has always been a concern in the digital space, with people unaware of their data being collected and sold. The main agenda for criticism is the fact that major players like Meta are leading the charge towards the new metaverse. Considering their previous history with privacy concerns of their users, that doesn’t simply fade away. The metaverse can lead to new issues in privacy for individuals as well as institutions. Privacy Other concerns around the metaverse are related to Thus, as a realistic 3D universe the metaverse blurs the gap between real and virtual worlds. Similar to gaming, addiction becomes a significant issue. There is a bigger addiction risk with the metaverse, since users are fully immersed in a virtual world, and while they are in the metaverse they easily lose track of time. mental health issues, addiction, and loss of connection with the physical world. Needless to say, while a secondary issue the metaverse remains, as for those who are not into tech or don’t belong to the crypto community, joining it is still problematic. Overcoming this flaw is important because without it the metaverse phenomenon will hardly reach mass adoption. UX issue Biometrics Biometrics as a technology for identifying a person based on the measurement and statistical analysis of its unique physical or behavioral characteristics is a phenomenon of high importance in modern society. It is a key to anchoring digital identity and the most suitable means of authenticating individuals in a reliable and fast way. Overall face shape, fingerprints, palm print, hand geometry, iris recognition, DNA, dental records, and even more subtle metrics like heartbeats or odor — modern technology can measure extremely complex inputs to find identity matches or verify identity. And experts argue that growth trends in mobile identity verification and remote onboarding will be sustained due to the recent pandemic spread which leads to the e-passport and health-passport markets explosion. Merits and demerits Biometrics provides numerous benefits. Thus, biometric technology is comparatively less time-consuming, dependable, user-friendly, and hard to falsify. However, there are some risks associated with biometric authentication. The main issues here are . security and privacy concerns In the last decades, major tech companies like have been constantly working on seamless user experiences without a hitch, bypassing the problems with login credentials. At the same time, users get used to trusting big tech to manage and collect their biometric data. These privacy concerns are multiplied by the fact that biometric data is regarded as highly sensitive since it may be linked to a single person. Apple Another major tech company patents captures users’ behavioral biometrics data. Specifically, pupil movements, body poses, and crumpled noses, which Meta would use to make digital avatars realistically animated. The patents by The Financial Times, according to their article Meta also intends to use biometric data to provide hyper-targeted advertising and sponsored content. Meta were reviewed What’s more, the company says it has created a new tool, , that will enable someone in Horizon, Meta’s metaverse, to import and create digital objects and features using only their voice. The voice assistant may not include a biometric authentication feature, but would rapidly accumulate a database of speech data, if successful. And an AI model for chatting with virtual assistants, something called Project , aims to enable natural conversations between assistants and people. Meta engineers also are working on software to all written languages and, separately, a universal speech translator for instant spoken-word translation. BuilderBot CAIRaoke translate Yet nothing is said about . biometric privacy at Meta Furthermore, even though biometric scanners are persistently improving in terms of quality, they can still create when an authorized user is not identified or authenticated, as well as false positives when an unauthorized person is recognized and authenticated. false negatives The most noteworthy merits and demerits of biometric identification are listed in the table above. In a nutshell, on the one hand, biometrics is , as well as , and remains a constant , on the other. and secure, flexible, affordable, trustable , and costly complex subject to attacks Q&A Before the world will dive headlong into the metaverse, the following questions need to be answered: How to protect your biometric data from malicious collection or theft? How to make sure that nobody else embodies your identity or metaverse avatar? How to ensure that you are not manipulated, and the person or company you interact with virtually is who you think they are? How to simplify the entrance to the metaverse and its UX for non-tech savvy users? Blockchain and biometrics are the answers, coming to the rescue here. Web3 and its backbone — have the potential to solve security issues and the need to trust personal data to major corporations when it comes to biometrics. blockchain Decentralization and transparency are the key concepts in Web3, that strive to increase the level of trust between the network’s participants, in the scenario when there is no third party controlling it. To minimize the risk of fraud, the metaverse operator shouldn’t have complete control over the biometric identity information and user data. The chosen identity authentication system could work with blockchain technology to help people stay in control of their personal data and how they are used. The blockchain would keep personal data under a user’s control because it cannot be changed once it’s on the public ledger. The service would just check against the blockchain whether the data user is genuine. This so-called self-sovereign identity attempts to solve the problem of providing personal info to service providers without risking data misusage. Linked with blockchain and protocols like zero-knowledge proofs are phenomena that are designed to bring privacy to the metaverse. encryption Precise, reliable, and handy can help protect metaverse users’ identities and the identities of others. Face recognition with liveness detection and iris scans are some of the most reliable biometric modalities. Regular biometric checks ensure that the metaverse user’s device such as VR goggles has not switched for another person. The system can have additional verification mechanisms, for example, through geolocation data. If the goggles are out of the usual space, further verification may be required. The idea is to validate a person’s authorized access with a combination of , such as a second software device, as seen in two-step verification. biometric identity verification biometrics and other authentication elements Furthermore, Biometrics is platform-agnostic, therefore users can leverage biometric verification for customer verification processes on all their devices — phones, goggles, or browsers. This makes biometrics very convenient when used for various gadgets. Compared with passwords, biometric authentication is faster and more seamless. With it, metaverse visitors have their biometric data at hand all the time, and it can’t be forgotten or lost. . biometrics enhances user experience On top of that, the appearance of items and agents metaverse users are interacting with can be adapted to their preferences based on data that they have shared. For example, eye tracking data can provide pupil dilation and gaze fixation data in response to visual stimuli, motion data can provide proxemic behavior and body language cues, and physiological data like EEG and skin conductance can provide levels of emotional activation. Additionally, facial tracking can also provide a window into an emotional response. These nonverbal cues can be fed into clever ML and AI algorithms to create personalized, idealized interactions. Blockchain and biometrics merge could have many pros for the metaverse. Blockchain technology biometric systems with some desirable characteristics such as immutability, accountability, availability, and universal access. Additionally, the integration of biometric technology is very beneficial for blockchain-based metaverses too, as it could significantly improve the current distributed digital identity schemes. In this case, an authentication protocol based on biometrics could significantly raise the current security level. could provide The merge: Web3 + biometrics Humanode is the world’s first blockchain project that utilizes a consensus mechanism based on crypto-biometric identification, to realize its goal of one human = one node = one vote network that brings Sybil resistance and innovative governance models to economics as a whole, and the crypto industry, in particular, using biometric technology. Humanode Humanode’s direct biometric API allows metaverses and other Dapps to integrate and enable unique online identities. Utilizing biometrics as one of its core technologies, Humanode creates the decentralized biometric identification layer that is not only used on the native Humanode platform but can be used in the metaverse. Due to s liveness detection technology, these biometric identifications ensure that the right person enters the metaverse and that he is a unique and real human being. FaceTec’ Humanode biometric identifications are likely to be tied in as an option for metaverse visitors’ identification in form of a wallet’s browser extension or as a full-fledged app. They will provide a simple way to interact with the metaverse and offer the most user-friendly interface for non-techy users. By only scanning their face, they will effortlessly access the metaverse, buy and sell tokens there, and sign transactions most accurately and securely. It is known that the collection of biometric data raises privacy concerns about the ultimate use of this information. The Humanode team is working on it. Besides biometrics and blockchain technologies in the broad sense, the project utilizes which is based on a stack of various disciplines and technologies such as cybersecurity, encryption, liveness detection, and zero-knowledge proofs. Once a user logs in to the Humanode, the 1 to n search and matching operation happens in an encrypted space, and because it is zero-knowledge based, the only piece of information that is searched for and is given out is if that user is a registered user or not. crypto-biometrics Avarta s biometric technology plays a critical role in another ambitious crypto project. In this case, the company’s partner is Singapore-based , a startup that is working to build an identity platform tailored to the DeFi and metaverse spaces. FaceTec’ Avarta Avarta aims is to establish a trust scoring system based on aggregated wallet data collected from multiple blockchain platforms while empowering end users with the ability to control what information they share with trusted third parties when seeking to gain access to regulated platforms or whitelists. Avarta is also looking to leverage geofencing and device scoring for its identity platform and has patented what it calls a “Dynamic PIN Lock” system. IriTech & IBCT In July 2022, with the Institute of Blockchain Technology (IBCT) to strengthen security for metaverse applications. The result is the Decentralized Identity Data Hub (DIDH) that runs on the blockchain. In practice, the joint offering will replace legacy security solutions like PINs with more secure iris biometrics for those using hardware wallets. Those wallets often give the owner no recourse if they forget their PIN, whereas the IriTech offering will allow owners to retrieve their secret backup seed with an iris recognition scan. In doing so, it will give owners a way to recover their accounts without exposing them to the security risk associated with any knowledge-based authenticator. IriTech teamed up The iris scan for the joint solution will be carried out with IriTech’s , which comes with liveness detection and is compatible with mobile devices. The goal, according to the two companies, is to give people more control over their personal information, in a manner that adheres to the principles of Self-Sovereign Identity (SSI). Data that is stored with the iris tech could theoretically be used for a variety of applications, ranging from healthcare and financial services to virtual and augmented reality. IriTech since its tech can be deployed alongside the iris tracker in a headset. IriKey technology expects VR and AR to be especially popular use cases Conclusion Both blockchain and biometrics technologies can mutually benefit each other and the metaverse, especially when combining them. Although the unified metaverse is still in its infancy, from all the above discussion, it is clear that biometrics alongside blockchain has the potential to make metaverse identity management decentralized, secure, private, simplified, and seamless, metamorphosing the landscape and accelerating adoption. Also Published Here

Biomeb

biomeb.com

-- employees

Since n.d.

COMPANY RANKING

Biomeb

EVERGREEN INDEX #1859

See more notable links about Biomeb

Apply to get your Tech Company News Page live on HackerNoon.com today!

Read More Tech Stories Related to #Biomeb

Biomeb

Biomeb

biomeb.com

-- employees

Since n.d.

COMPANY RANKING

Biomeb

EVERGREEN INDEX #1859

Related CompaniesRank

Biomeb Story MentionsComplete List

See more notable links about Biomeb

Apply to get your Tech Company News Page live on HackerNoon.com today!

Read More Tech Stories Related to #Biomeb

Biomeb