question: Why the biometric verification systems don't use fingerprint sensors from smart phones why they are different ?
comment: Some of them do use very similar fingerprint sensors, but usually for 4-5 fingers. There are many different models. Is there a particular one that has you wondering?
passages: BULLET::::- Stability requires that fingerprints remain the same over time. However, by definition browser configuration preferences are not tamper proof. For example, if one measured attribute is whether the browser has cookies on or off, then a simple change of that setting is sufficient to change the fingerprint. One remedy is to reduce the number of parameters collected to only those that are very unlikely to change; however, this is likely to reduce diversity, as fewer parameters are being measured.
  
  Section::::Active vs passive collection.
  
  Fingerprinting methods range from passive to active.
   Two of the first smartphone manufacturers to integrate fingerprint recognition into their phones were Motorola with the Atrix 4G in 2011, and Apple with the iPhone 5S on September 10, 2013. One month after, HTC launched the One Max, which also included fingerprint recognition. In April 2014, Samsung released the Galaxy S5, which integrated a fingerprint sensor on the home button.
   A 30-page white paper titled "Risks and Opportunities of Contactless Biometrics" identified "spoofing as a serious limitation, and ranks "what people know" (password, challenge question) and "what they have" (keycard, identify "token") higher than "biometrics".
  
  Although it ranks facial recognition and iris recognition ahead of contactless fingerprint identification, it is the fingerprint that ranks hightest of the three for high-security situations. The whitepaper noted that the Canadian Border Services Agency was planning to utilize a combination of facial recognition and fingerprints.
  
  One such experiment used an assist: using flight manifests to compare faces with passport photos of those listed.
   Section::::Uses.:Handheld and personal devices.
  
  Fingerprint sensors can be found on mobile devices. The fingerprint sensor is used to unlock the device and authorize actions, like money and file transfers, for example. It can be used to prevent a device from being used by an unauthorized person.
  
  Section::::Present day biometric devices.
  
  Section::::Present day biometric devices.:Personal signature verification systems.
   Biometric security vendors complying with data privacy laws and regulations (including Apple FaceID, Samsung, Google) therefore focused their efforts on the simpler 1:1 verify problem and were unable to overcome the large computational demands required for linear scan to solve the 1:many identify problem.
   In practice neither diversity nor stability is fully attainable, and improving one has a tendency to adversely impact the other.
  
  BULLET::::- Diversity requires that no two machines have the same fingerprint. However, large numbers of machines are likely to have exactly the same configuration data and thus the same fingerprint. This is particularly true in the case of factory installed operating systems. One remedy is to use a scripting language to harvest a large numbers of parameters from the client machine; however, this is likely to reduce stability, as there are more parameters that may change over time.
   At WWDC 2018 Apple announced that Safari on macOS Mojave "presents simplified system information when users browse the web, preventing them from being tracked based on their system configuration."
  
  Section::::Essentials.
  
  Motivation for the device fingerprint concept stems from the forensic value of human fingerprints. In the "ideal" case, all web client machines would have a different fingerprint value (diversity), and that value would never change (stability). Under those assumptions, it would be possible to uniquely distinguish between all machines on a network, without the explicit consent of the users themselves.
   Contactless fingerprint technology is the third generation: Wet-ink was followed by an option for "optics-based ... light reflected from the tops of fingerprints on a plate."
  
  As of 2017, "face recognition technologies on the whole are in general less accurate than fingerprinting." Aging, variations in pose and problems with illumination have caused the former to have "higher error rates."
  
  Section::::History.
  
  The use of lasers to detect fingerprints already existed in the 1980s, but this was limited to matching objects to fingerprints on file.
  
  Section::::USA Public/Private Contactless study.
   Since 2017, Fingerprint cards has also been working on diversifying their product portfolio with alternative authentication solutions such as face and iris recognition. 
  
  Section::::Competitors.
  
  Due to the technological advancement and increased interest in biometric solutions during the 2010s, competition has grown in the fingerprint sensor market. Fingerprint Cards' market share has decreased in the past years as a number of new companies has emerged in the market and created new competition. As of 2019, The top players of the global fingerprint sensor market are; 
  
  Section::::Criticism and Controversies.
  
  Section::::Criticism and Controversies.:2012.
   BULLET::::- Biometric methods promise authentication based on unalterable personal characteristics, but currently (2008) have high error rates and require additional hardware to scan, for example, fingerprints, irises, etc. They have proven easy to spoof in some famous incidents testing commercially available systems, for example, the gummie fingerprint spoof demonstration, and, because these characteristics are unalterable, they cannot be changed if compromised; this is a highly important consideration in access control as a compromised access token is necessarily insecure.
   Fingerprint matching has an enormous computational burden. Some larger AFIS vendors deploy custom hardware while others use software to attain matching speed and throughput. In general, it is desirable to have, at the least, a two-stage search. The first stage will generally make use of global fingerprint characteristics while the second stage is the minutia matcher.
   Multimodal biometric systems use multiple sensors or biometrics to overcome the limitations of unimodal biometric systems. For instance iris recognition systems can be compromised by aging irises and electronic fingerprint recognition can be worsened by worn-out or cut fingerprints. While unimodal biometric systems are limited by the integrity of their identifier, it is unlikely that several unimodal systems will suffer from identical limitations. Multimodal biometric systems can obtain sets of information from the same marker (i.e., multiple images of an iris, or scans of the same finger) or information from different biometrics (requiring fingerprint scans and, using voice recognition, a spoken passcode).
   All the proposed methods can be grouped into two major families: solid-state fingerprint readers and optical fingerprint readers. The procedure for capturing a fingerprint using a sensor consists of rolling or touching with the finger onto a sensing area, which according to the physical principle in use (optical, ultrasonic, capacitive, or thermal) captures the difference between valleys and ridges. When a finger touches or rolls onto a surface, the elastic skin deforms. The quantity and direction of the pressure applied by the user, the skin conditions and the projection of an irregular 3D object (the finger) onto a 2D flat plane introduce distortions, noise, and inconsistencies in the captured fingerprint image. These problems result in inconsistent and non-uniform irregularities in the image. During each acquisition, therefore, the results of the imaging are different and uncontrollable. The representation of the same fingerprint changes every time the finger is placed on the sensor plate, increasing the complexity of any attempt to match fingerprints, impairing the system performance and consequently, limiting the widespread use of this biometric technology.
   Section::::Problems with present day biometric devices.:Accuracy.
   This may allow a remote application to detect and prevent online identity theft and credit card fraud, but also to compile long-term records of individuals' browsing histories even when they're attempting to avoid tracking, raising a major concern for internet privacy advocates. 
  
  Some computer security experts consider the ease of bulk parameter extraction offered by web browsers to be a security hole.
  
  Section::::History.
   A pending court case defined failures of even 1% to be "high risk" if it results in denials of government benefits.
  
  Section::::USA DOJ report.
  
  A 56-page report titled "Contactless Fingerprint Technologies Assessment" was funded in 2010, and version 2 of the report was "made ... available" in 2014 online even though it "has not been published."
  
  After describing 13 R&D projects in various stages of incompleteness, it identifies four "contactless fingerprint existing products." 
  
  BULLET::::- The first company's product attaches to a PC via USB and "is designed for indoor use only."
   Fingerprint image acquisition is considered to be the most critical step in an automated fingerprint authentication system, as it determines the final fingerprint image quality, which has a drastic effect on the overall system performance. There are different types of fingerprint readers on the market, but the basic idea behind each is to measure the physical difference between ridges and valleys.
   By 2017 Hewlett Packard, Asus, Huawei, Lenovo and Apple were using fingerprint readers in their laptops. Synaptics says the SecurePad sensor is now available for OEMs to start building into their laptops. In the newest smartphones, the fingerprint reader is being integrated into the whole touchscreen display instead of as a separate sensor.
  
  Section::::Other uses.
  
  Section::::Other uses.:Welfare claimants.
  
  It has been alleged that taking the fingerprints of welfare recipients as identification serves as a social stigma that evokes cultural images associated with the processing of criminals.
  
  Section::::Absence or mutilation of fingerprints.
   BULLET::::- Mobil Phone security: Software downloaded to "nearly any mobile phone that has a camera" can authenticate fingerprints.
  
  Section::::Research.
  
  A 2012 technology review of fingerprint identification with 95 citations only had three regarding contactless/touchless research.
  
  A 2017 NIST designed to see how effectively members of the public could use a "contactless fingerprint" device in a simulated airport situation found that about half of the participants could not successfully validate their fingerprints on their first try. The study added a training video, and that improved results. The report considered it "encouraging for the employment of touchless finerprint technology."
  
  Section::::External links.
   Future research on biometric cryptosystems is likely to focus on a number of remaining implementation challenges and security issues involving both the fuzzy representations of biometric identifiers and the imperfect nature of biometric feature extraction and matching algorithms. And, unfortunately, since biometric cryptosystems can, at the current time, be defeated using relatively simple strategies leveraging both weaknesses of the current systems (the fuzzy representations of biometric identifiers and the imperfect nature of biometric feature extraction and matching algorithms), it is unlikely that these systems will be able to deliver acceptable end-to-end system performance until suitable advances are achieved.
   Section::::Types of biometric authentication.
  
  BULLET::::- Fingerprint recognition - Fingerprint is the most widely used form of authentication where the pattern of a user’s fingertip is used. It can be deployed in a broad range of environments and provides flexibility and increased system accuracy by allowing users to enrol multiple fingers in the template system.
   More traditional means of access control include token-based identification systems, such as a driver's license or passport, and knowledge-based identification systems, such as a password or personal identification number. Since biometric identifiers are unique to individuals, they are more reliable in verifying identity than token and knowledge-based methods; however, the collection of biometric identifiers raises privacy concerns about the ultimate use of this information.
  
  Section::::Biometric functionality.
   BULLET::::- Tamperproof in that the feature vector’s one-way encryption prevents unauthorized changes and does not use systems that control rights to the security monitor code, configuration and data.
  
  Section::::History.
  
  Section::::History.:Implicit authentication and private equality testing.
  
  Unsecure biometric data are sensitive due to their nature and how they can be used. Implicit authentication is a common practice when using passwords, as a user may prove knowledge of a password without actually revealing it. However, two biometric measurements of the same person may differ, and this fuzziness of biometric measurements renders implicit authentication protocols useless in the biometrics domain.
   Section::::Benefits of biometric devices over traditional methods of authentication.
  
  BULLET::::- Biometric data cannot be lent and hacking of Biometric data is complicated hence it makes it safer to use than traditional methods of authentication like passwords which can be lent and shared. Passwords do not have the ability to judge the user but rely only on the data provided by the user, which can easily be stolen while Biometrics work on the uniqueness of each individual.
   example for credit cards), or with more specific areas such as identity
  
  card verification, checks for duplicate enrollment, passports, or physical
  
  access control in a commercial environment or for airport employees or
  
  merchant seamen wishing to go on-shore at their arrival port.
  
  Whilst today a system is commonly built using a single device for a
  
  single application, it is likely that in the long term many such
  
  applications will interact (securely, and via a network) with a common
  
  set of trusted devices (with various security policies and certificates).
  
  It is also expected that future biometrics applications will use
  
presuppositions: Biometric verification systems are different than fingerprint sensors on smartphones.
corrections: Some biometric verification systems use similar fingerprint sensors that are used in smartphones.
raw_presuppositions: Biometric verification systems are different than fingerprint sensors on smartphones. Biometric verification systems are different than fingerprint sensors on smartphones.
raw_corrections: Some biometric verification systems use similar fingerprint sensors that are used in smartphones. Some biometric verification systems use similar fingerprint sensors to smartphones.