{"id":6517,"date":"2024-05-06T14:05:00","date_gmt":"2024-05-06T12:05:00","guid":{"rendered":"https:\/\/innovatrics.com\/trustreport\/?p=6517"},"modified":"2024-06-04T18:10:34","modified_gmt":"2024-06-04T16:10:34","slug":"how-biometric-identity-verification-protects-passengers-usingride-hailing-apps","status":"publish","type":"post","link":"https:\/\/innovatrics.com\/trustreport\/how-biometric-identity-verification-protects-passengers-usingride-hailing-apps\/","title":{"rendered":"How biometric identity verification protects passengers using<br>ride-hailing apps"},"content":{"rendered":"\n<figure class=\"wp-block-video aligncenter desktop-only\"><video autoplay loop muted src=\"https:\/\/innovatrics.com\/trustreport\/wp-content\/uploads\/2024\/04\/innovatrics-4-v2-RESIZE-final-1.mp4\"><\/video><\/figure>\n\n\n\n<figure class=\"wp-block-video aligncenter mobile-only\"><video autoplay loop muted src=\"https:\/\/innovatrics.com\/trustreport\/wp-content\/uploads\/2024\/04\/innovatrics-4-v1-RESIZE-final-1x1-2.mp4\"><\/video><\/figure>\n\n\n\n<div class=\"wp-block-columns bottom0\">\n<div class=\"wp-block-column margin\" style=\"flex-basis:33.33%\"><div class=\"contributor\">\n    <img src=\"https:\/\/innovatrics.com\/trustreport\/wp-content\/uploads\/2023\/06\/viktor-bielko.jpg\" class=\"contributor__image\" alt=\"\">\n    <div class=\"contributor__text\">\n        <p><b>Viktor Bielko<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Product manager at Innovatrics<\/span><\/p>\n    <\/div>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<p class=\"has-medium-font-size\"><strong><strong><strong>To get home one night, you order a taxi through a ride-hailing app. You don\u2019t check who your driver is because you don\u2019t have to. With driver face verification and liveness check algorithms, you know that the ride-hailing app continuously verifies thousands of drivers, making all the rides you take safe.&nbsp;<\/strong><\/strong><\/strong><\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns bottom0\">\n<div class=\"wp-block-column\" style=\"flex-basis:33.33%\"><\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<p>Ride-hailing apps made earning money as a driver and saving money as a passenger easy, and all just a few clicks away. But with the growing popularity of these services and increasing numbers of registered drivers, ensuring passenger safety has become a priority for several of Innovatrics\u2019 clients: companies that offer ride-sharing through smartphone apps, and who are prioritising reliable driver verification worldwide through the use of biometrics.<\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns top0\">\n<div class=\"wp-block-column margin\" style=\"flex-basis:33.33%\"><\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<h2>Boosting trust by verifying drivers<\/h2>\n\n\n\n<p>Consider this scenario: It&#8217;s late at night and you need a ride home. You step into a taxi, and it speeds off. Do you ever pause to think about the identity and trustworthiness of your driver? These are the critical concerns that responsible ride-hailing apps centre their businesses around. They work hard to ensure you feel safe, because their business relies on your trust.&nbsp;<\/p>\n\n\n\n<p>This trust is not to be underestimated. These companies expend significant resources in terms of time and finances to ensure passenger safety. Driver verification, i.e. making sure you get a ride from the same person displayed in the app, is one of the most important aspects of building and maintaining trust.&nbsp;<\/p>\n\n\n\n<p>However, with the prevalence of fake accounts and instances of driver impersonation, how do these apps enhance their security and deepen trust in their services?&nbsp;<\/p>\n\n\n\n<blockquote class=\"wp-block-quote\"><p><em>\u201cThe problem is that some drivers don&#8217;t follow the rules properly and can get banned. Then, some try to find a way around the ban by creating new accounts.\u201d&nbsp;<\/em><\/p><cite><strong>Viktor Bielko, Innovatrics<\/strong><\/cite><\/blockquote>\n\n\n\n<p><\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\" style=\"flex-basis:33.33%\">\n<p class=\"has-small-font-size\"><strong>Test run<\/strong><\/p>\n\n\n\n<p class=\"has-small-font-size\">Ride-hailing apps that collaborate with Innovatrics always test how well Innovatrics&#8217; algorithms work. They do this by sending a huge dataset of pictures to see how the algorithms handle three tasks: checking if a selfie matches an ID, comparing one selfie to another, and identifying photos in a database.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<h2>Uncovering fake accounts with biometrics<\/h2>\n\n\n\n<p>Ride-hailing companies check their drivers regularly and ban them from working with the service if they fail to provide an up-to-date ID, have committed a crime in recent years, behave inappropriately, or receive persistently low ratings from passengers. The problem comes when these banned drivers try to side-step the ban:<\/p>\n\n\n\n<p><em>\u201cSome drivers don&#8217;t follow all the rules properly, which leads to them getting banned. They then often create new accounts to find a way around the ban, impersonating their family or friends. We consider this to be a serious safety issue that can be solved with biometric face verification,\u201d<\/em> explains Viktor Bielko, product manager of the DOT (Digital Onboarding Toolkit) product in Innovatrics.<\/p>\n\n\n\n<p><em>A reliable and powerful remote identity verification system enables the ride-hailing apps to safely verify the identity of each driver at any point in time. The verification process works as follows:&nbsp;<\/em><\/p>\n\n\n\n<ul><li>any driver can receive a notification at any given moment asking them to safely stop and take a selfie,<\/li><li>the selfie is then compared to the driver&#8217;s ID,<\/li><li>at the same time, the system performs a liveness check.<\/li><\/ul>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\" style=\"flex-basis:33.33%\">\n<p class=\"has-small-font-size\">The selfie to ID verification and liveness detection is part of Innovatrics&#8217; digital onboarding tool <a href=\"https:\/\/www.innovatrics.com\/digital-onboarding-toolkit\/\">DOT<\/a>, which is a software that enables facial registration, extracts data from IDs, performs facial comparisons and verifies the <a href=\"https:\/\/www.innovatrics.com\/digital-onboarding-toolkit\/liveness-detection\/\">liveness<\/a> of each registered individual.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<h2>Liveness detection \u2013 the easiest way to avoid spoofing<\/h2>\n\n\n\n<p>The role of a liveness check is to make sure the system is dealing with actual people, not fake images. To illustrate its importance, this is a typical scenario where a liveness check proves critical: imagine a driver who is banned because of consistently bad reviews. They don&#8217;t want to lose their income, so they create a new account in their friend&#8217;s name and ID. They also have a few photos of this friend on their phone. When they\u2019re prompted by the system to verify their identity by taking a selfie, they simply use the friend\u2019s photo, and that\u2019s it, right? Well, not with a proper liveness check.&nbsp;<\/p>\n\n\n\n<p><em>\u201cA presentation attack occurs when someone tries to trick the system by using a fake representation instead of their real face. To detect such attacks, we train our detection algorithm on huge amounts of data to uncover the use of 2D or 3D masks, paper photos or images of screens. That way, we can stop potential fraud or identity thefts,\u201d<\/em> explains Viktor.&nbsp;<\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns bottom0\">\n<div class=\"wp-block-column margin\" style=\"flex-basis:33.33%\">\n<hr class=\"wp-block-separator\"\/>\n\n\n\n<p><strong>Proof of reliability&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-small-font-size\">Innovatrics&#8217; liveness detection algorithm, which is trained to detect identity fraud, has passed tests by iBeta \u2013 an independent biometrics testing lab. The submission has attained the highest possible level of accuracy in <a href=\"https:\/\/www.innovatrics.com\/awards\/level-1-ibeta-presentation-attack-detection-conformance\/?utm_source=Trust-report&amp;utm_medium=Site&amp;utm_campaign=Unfair-AI&amp;utm_content=Molcany&amp;_ga=2.8019185.2115538941.1699524269-757285209.1669369528\">iBeta testing<\/a>, correctly detecting all 1,500 attempted spoofs and accepting all of the genuine logins. Simply put, the algorithm rejects 100% of false presentations and doesn\u2019t mistakenly reject anyone who is indeed present.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<h2>The most common presentation attacks that<br>ride-hailing apps face<\/h2>\n\n\n\n<p>It&#8217;s crucial for ride-hailing services to tackle these common tricks to keep their platform secure and make sure everyone has a safe and trustworthy experience, whether you&#8217;re a passenger or a driver.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large width640\"><img loading=\"lazy\" width=\"10768\" height=\"11848\" src=\"https:\/\/innovatrics.com\/trustreport\/wp-content\/uploads\/2024\/05\/graf2-3.png\" alt=\"\" class=\"wp-image-7368\" srcset=\"https:\/\/innovatrics.com\/trustreport\/wp-content\/uploads\/2024\/05\/graf2-3.png 10768w, https:\/\/innovatrics.com\/trustreport\/wp-content\/uploads\/2024\/05\/graf2-3-273x300.png 273w, https:\/\/innovatrics.com\/trustreport\/wp-content\/uploads\/2024\/05\/graf2-3-273x300@2x.png 546w\" sizes=\"(max-width: 10768px) 100vw, 10768px\" \/><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns top0 bottom0\">\n<div class=\"wp-block-column\" style=\"flex-basis:33.33%\">\n<p class=\"has-small-font-size\"><strong>Active and passive liveness checks&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-small-font-size\">There are two types of liveness detection:<\/p>\n\n\n\n<p class=\"has-small-font-size\"><em>Active <\/em>check is based on action. You ask a person to perform a certain task, for example, smile, follow the dot with their eyes, etc.&nbsp;<\/p>\n\n\n\n<p class=\"has-small-font-size\"><em><em>Passive<\/em> <\/em>check evaluates liveness without the customer ever noticing it. It makes the interaction simple and hard to spoof as the attacker does not know if and when liveness verification has transpired.<em>&nbsp;<\/em><\/p>\n\n\n\n<p class=\"has-small-font-size\">The passive approach to liveness detection considers hundreds of variables, such as light, shadows, the texture of the skin, and other significant factors. Active check on top of it uses multiple photos, where a difference between the photos has to correspond with the action required from the user.<\/p>\n\n\n\n<p><\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<h2>The biggest challenge for verification \u2013 photo quality<\/h2>\n\n\n\n<p><em>One of the issues that makes it difficult, and sometimes even impossible, for the algorithm to perform the liveness check and verify the driver, is low photo quality. <em>\u201cComparing selfies with IDs is not the problem, photo quality is. Drivers usually take selfies inside the car in bad lighting conditions, and often during the night. Sometimes they take extremely close-up photos of their face. Other times it&#8217;s the opposite; the face is too small,\u201d <\/em>explains Viktor.&nbsp;<\/em><\/p>\n\n\n\n<p>However, thanks to the close cooperation with the ride-hailing apps, Innovatrics identified these problems at the very beginning of the project. The R&amp;D team created an analysis that summarised acceptable thresholds of quality to ensure reliable verification. The team analysed the photos&#8217; brightness, contrast, sharpness and other attributes.&nbsp;<\/p>\n\n\n\n<p>Another issue ride-hailing companies struggle with is quick feedback. The goal is to keep the app as small as possible so it doesn\u2019t take up a lot of space on the driver&#8217;s device. For this reason, the verification process occurs on remote servers, not in the app, meaning that feedback on the quality of the photo is not in real-time. If incorrectly denied, drivers must wait for information about what went wrong. There is an update in implementation that makes this process smoother and more user-friendly.&nbsp;<\/p>\n\n\n\n<blockquote class=\"wp-block-quote\"><p><em>\u201cComparing selfies with IDs is not the problem, photo quality is. Drivers usually take selfies inside the car in bad lighting conditions, and often during the night. Sometimes, they take extremely close-up photos of their face. Other times it&#8217;s the opposite; the face is too small.\u201d<\/em><\/p><cite><strong>Viktor Bielko, Innovatrics<\/strong><\/cite><\/blockquote>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns top0\">\n<div class=\"wp-block-column margin\" style=\"flex-basis:33.33%\"><\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<h2>Servers are key to good performance<\/h2>\n\n\n\n<p>As many ride-hailing companies use servers for the verification process, the right server configuration is essential. <em>\u201cIt is important to have the hardware set up for high availability, so in case of any errors, other servers can cover for the lost power,\u201d<\/em> explains Viktor. It is also important to know how many operations the servers need to be able to manage.&nbsp;<\/p>\n\n\n\n<p>In this scenario, verification is evenly distributed over time, as companies manage notifications independently. Presently, the system handles approximately a hundred driver verifications per minute.<\/p>\n\n\n\n<h2>Making the product better&nbsp;<\/h2>\n\n\n\n<p>Innovatrics offers ID document reading and OCR algorithm that reads text and extracts faces from approximately 300 different types of official documents and IDs. However, the solution faced a challenge due to the diverse range of nationalities and documentation of registered drivers. <em>\u201cIn response, we delivered the algorithm to only look for the face portrait and omit the document reading. It makes the whole process easier and faster,\u201d<\/em> adds Viktor.<\/p>\n\n\n\n<p>Thanks to partnering with ride-hailing companies, Innovatrics improved its face recognition and liveness testing product.&nbsp;Many of these partnerships are still ongoing, with the completion of the verification and liveness check marking the initial phase, and the collaborations progressing into the second phase with 1:1 (selfie vs. selfie) verification, and subsequently the third phase, where the identification is based on database information, ensuring continuous improvement.<\/p>\n<\/div>\n<\/div>\n\n\n\n<p class=\"has-text-color has-small-font-size\" style=\"color:#7c878e\"><strong>AUTHOR<\/strong>: Jana Nov\u00e1kov\u00e1<br><strong>COVER:<\/strong> Elizabeth Bugyiov\u00e1<br><strong>COVER ANIMATION:<\/strong> Dominik Prokop<br><strong>INFOGRAPHICS: <\/strong>Aleksandar Peri\u0161i\u0107<\/p>\n\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\" style=\"flex-basis:33.33%\"><\/div>\n\n\n\n<div class=\"wp-block-column\" style=\"flex-basis:66.66%\">\n<p><strong><em>Sources<\/em><\/strong><\/p>\n\n\n\n<ol><li><a href=\"https:\/\/www.wired.com\/story\/secret-history-facial-recognition\/\">Secret History of Facial Recognition<\/a><\/li><li><a href=\"https:\/\/www.weforum.org\/agenda\/2021\/10\/facial-recognition-technology-law-enforcement-human-rights\/\">Police super-recognizers<\/a><\/li><li><a href=\"https:\/\/habs.uq.edu.au\/article\/2023\/07\/ai-and-human-team-best-facial-recognition\">AI and Human Team<\/a><\/li><li><a href=\"https:\/\/gala.gre.ac.uk\/id\/eprint\/29529\/3\/29529%20DAVIS_Capitalizing_On_The_Super-recognition_Advantage_%28AAM%29_2020.pdf\">Capitalizing On The Super-recognition<\/a><\/li><li><a href=\"https:\/\/gala.gre.ac.uk\/id\/eprint\/29529\/3\/29529%20DAVIS_Capitalizing_On_The_Super-recognition_Advantage_%28AAM%29_2020.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">Human Super-recognizers See Faces Better Than AI<\/a><\/li><li><a href=\"https:\/\/www.alliedmarketresearch.com\/facial-recognition-market#:~:text=The%20global%20facial%20recognition%20market,16.4%25%20from%202023%20to%202032\" target=\"_blank\" rel=\"noreferrer noopener\">Market Research<\/a><\/li><li><a href=\"https:\/\/recfaces.com\/articles\/facial-vs-fingerprints-biometrics\" target=\"_blank\" rel=\"noreferrer noopener\">Facial Vs. Fingerprint Biometrics<\/a><\/li><li><a href=\"https:\/\/www.information-age.com\/the-future-of-biometric-payments-123507398\/\">The Future Of Biometric Payment<\/a><\/li><li><a href=\"https:\/\/www.juniperresearch.com\/pMobile%20Biometrics%20Authentification%20Of%20Payments%20\">Mobile Biometrics Authentication Of Payments<\/a><\/li><li><a href=\"about:blank\">How Facial Recognition Works<\/a><\/li><li><a href=\"https:\/\/www.forbes.com\/sites\/ariannajohnson\/2023\/05\/25\/racism-and-ai-heres-how-its-been-criticized-for-amplifying-bias\/?sh=2edae8e8269d\">Racism and AI<\/a><\/li><li><a href=\"https:\/\/www.media.mit.edu\/projects\/gender-shades\/overview\/\">Gender Shades<\/a><\/li><\/ol>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>To get home one night, you order a taxi through a ride-hailing app. You don\u2019t check who your driver is because you don\u2019t have to. With driver face verification and liveness check algorithms, you know that the ride-hailing app continuously verifies thousands of drivers, making all the rides you take safe. <\/p>\n","protected":false},"author":14,"featured_media":7077,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[33,66,56],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v15.6.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How biometric identity verification protects passengers usingride-hailing apps - Innovatrics<\/title>\n<meta name=\"description\" content=\"To get home one night, you order a taxi through a ride-hailing app. You don\u2019t check who your driver is because you don\u2019t have to. 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