Abstract:
The present invention is directed to a method and system for defeating replay attacks against biometric authentication systems by randomly prompting the subject to adjust a part of their body in some measurable way. The timing of these adjustments would be used to verify that the biometric input is coming from a live subject and not a recording. One embodiment of the design would include a commodity camera-equipped mobile device ( 130 ) connected to an authentication server ( 110 ) via the Internet ( 120 ). In this embodiment an encrypted video stream of the subject—for example his or her hand ( 140   a )—would be established from the mobile device to the authentication server. The authentication server would generate a unique series of time delays, at which intervals a prompt—for example to extend or retract a specific finger—would be relayed from the server to the mobile device and subsequently the subject. The subject&#39;s coordinated response to these timed prompts—and only these timed prompts—would be measured by the authentication server. By comparing biometric features from the video stream—for example measurements of finger dimensions—to the known values for the subject in a database the authentication server will decide whether or not to authenticate the user.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     Not Applicable 
     FEDERALLY SPONSORED RESEARCH 
     Not Applicable 
     SEQUENCE LISTING OR PROGRAM 
     Not Applicable 
     BACKGROUND 
     1. Field 
     This application relates to biometric authentication systems, specifically those that verify the identity of an individual by measuring one or more physical attributes of a person and making a comparison to stored measurements of known persons. 
     2. Prior Art 
     Authentication, along with confidentiality and integrity, is one of the fundamental requirements of any secure system. Typically authentication is performed by one or more of three major ‘factors’: (1) something a user knows (e.g.—a password, pass code or pass phrase), (2) something a user has (e.g.—a physical key, card, bar code, mobile phone or certificate) and (3) something a user is (e.g.—a person&#39;s physical characteristic such as DNA, iris, hand, skin texture, voice, face, fingerprint or blood vessel patterns). These three factors are often referred to as knowledge-based, token-based and biometric-based authentication factors, respectively. Demand for multifactor authentication systems (a.k.a—‘fused,’ ‘dual’ or ‘combinatoric’ systems) that combine one or more of these three factors is increasing because they present a higher obstacle to criminals. Such techniques are also becoming easier to implement thanks to the wide availability of mobile phones, PDAs and other such devices. For example, modern bank web sites often send a text message to users&#39; mobile phones containing a random code that they must type into a web form. This combines a token-based factor (i.e.—possession of the phone) with a knowledge based factor (i.e.—the standard password prompt) in a manner that is cheap enough to be widely deployed. 
     However, purpose-built biometric authentication hardware is not widely deployed among consumers and therefore biometrics are infrequently used over the web. Furthermore, biometric authentication systems are particularly vulnerable to replay attacks in which a criminal makes a copy of the real user&#39;s features and later presents them to the authentication device. For example, an attacker can steal a photograph of a user&#39;s eye and present it to an eye scanner, or intercept data in transit across a network and re-transmit it to the authentication server at a later date. This problem is compounded by the fact that in the web usage model the authentication system is under the physical control of the untrusted user. However, the embodiments of the present invention are not susceptible to such simple attacks and could therefore be implemented with widely deployed commodity hardware such as mobile phones, laptops, tablet computers or PDAs. This capability will enable businesses and individuals to conduct a larger fraction of their transactions over the Internet due to the improved security. 
     Although biometric and multifactor authentication systems exist in the prior art, none are simultaneously deployable on commodity hardware and resistant to replay attacks. All are therefore poorly suited to wide deployment over the Internet. U.S. Pat. No. 7,766,223 to Stephen M. Mello et al describes a multifactor authentication system involving voice prints for biometric factors. However, no mention is made of replay attacks and therefore the biometric factor can be defeated easily using an audio recording. In fact this patent refers to ‘the’ keyword or phrase used for voice authentication indicating that it is static and unchanging and therefore vulnerable to replay attacks. Furthermore voice is the only biometric authentication factor addressed. U.S. Pat. No. 7,373,515 to William N. Owen describes a multifactor authentication system but makes no mention of securing the biometric reader device or defeating replay attacks. U.S. Pat. No. 6,941,001 to Bolle et. al. describes a method for defeating replay attacks against fingerprint biometrics, but requires a ‘combined pointing and fingerprint recognition device’ which is rarely, if ever, available on commodity hardware due to cost. Furthermore, fingerprints are the only biometrics addressed and no claim is made upon the technique of randomly stimulated user input claimed here. In fact, the method uses a previously defined ‘gestural password’ which is not random and again, is therefore susceptible to replay attacks. 
     U.S. patent application Ser. No. 11/644,573 by Michael Baentsch et. al. asserts that there will always be natural, random fluctuations in biometric data and accordingly rejects authentication data that looks ‘too close’ to the expected template. The technique attempts to differentiate between malicious manipulation of an image of the subject and statistically expected variations. However, this means that the technique would be vulnerable to a stolen video of the subject, which would contain the subject&#39;s natural and therefore statistically expected movements. No discussion of resistance to video replay attacks is present in the patent. 
     There are several types of replay attack detection systems that rely on timestamps, ‘numbers used once’ (nonce) and digests (hash functions) of those values—U.S. Pat. Nos. 6,957,339 (2002), 7,178,025 (2003) and U.S. patent application Ser. Nos. 10/280,732 (2002) and 11/094,452 (2005). However, these approaches only address the security of data after it has been collected by the reader—which is inherently trusted in these architectures. No method is presented for ensuring that the person is currently alive and present at the reader. This assurance is critical for the purposes of secure web commerce since large numbers of uncontrolled devices will be used. For example, if an attacker successfully replayed an image of an iris to a scanner device utilizing nonces and timestamps, the device would generate a new nonce and timestamp for the data and blindly send it along to the authentication server. 
     U.S. Pat. No. 7,027,617 to Robert Frischholz describes the display of objects at random positions on a computer screen and estimating the line of sight of an eye looking at the objects to defeat replay attacks. However, the small screens of commodity mobile devices make this technique unfeasible for that important class of devices. Furthermore, eye-based techniques are the only methods addressed by the patent, and the detection of prompted blinking or finger extension is not addressed. 
     3. Advantages 
     An advantage of the method described in the present application is that randomized integrity checking is integrated with the biometric measurement itself. This is in contrast to other systems that use non-biometric factors to defeat replay attacks against the biometric factor, thus marginalizing the benefit of biometrics. The present method achieves this by prompting the user to adjust their biometric input at randomly generated time intervals, e.g.—by blinking, extending or retracting fingers, reciting prompted words, etc. These prompts are generated by the trusted authentication server, and their responses are generated by the user requesting authentication. Since both entities are external to the reader system its integrity is not critical for the system to work, making commodity mobile devices suitable as readers. The reader device essentially becomes a data capture and transport mechanism and is no more trusted than any given router on the transport network connecting the reader to the authentication server. This enables authentication in e-commerce applications to a far larger degree than in the prior art because users will be able to use equipment they already own to conduct secure transactions on the web. 
     Another advantage to the approach described here is that the user responses are captured by the same sensor that is used to capture the biometric data. This ensures that the person in control of the biometric feature is alive and present at the reader. This would not be the case if, for example, one was required to scan a fingerprint on a reader and subsequently respond to a random sequence of commands on a computer touch pad. The sequence of command responses could be entered by a different finger than the scanned finger. 
     The randomness of the user prompts ensures the integrity of the biometric authentication so that it can legitimately add security when used as one factor in a multifactor system. Systems such as U.S. Pat. No. 7,039,812 to Citicorp Development Center, Inc. that require the user to always enter a known sequence of biometric inputs would be vulnerable to replay attacks precisely because the sequence is known. Such attempts at combining knowledge based and biometric authentication factors would be vulnerable to simple replay attacks using video or other recordings. 
     BRIEF SUMMARY OF THE INVENTION 
     The present invention is directed to a method and system for defeating replay attacks against biometric authentication systems. This is achieved by randomly prompting the subject to adjust a part of their body in some measurable way. The timing of these adjustments would be used to verify that the biometric input is coming from a live subject and not a recording. One embodiment of the design would include a commodity camera-equipped mobile device connected to an authentication server via the Internet. In this embodiment an encrypted video stream of the subject—for example his or her hand—would be established from the mobile device to the authentication server. The authentication server would generate a unique series of time delays, at which intervals a prompt—for example to extend or retract a specific finger—would be relayed from the server to the mobile device and subsequently the subject. The subject&#39;s coordinated response to these timed prompts—and only these timed prompts—would be measured by the authentication server. By comparing biometric features from the video stream—for example measurements of finger dimensions—to the known values for the subject in a database the authentication server will decide whether or not to authenticate the user. This authentication would only be approved if the features match the known values and the responses to the prompts match the timing of the prompts. 
    
    
     
       DRAWINGS 
       Figures 
       The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of the specification. The drawings illustrate several embodiments of the invention and together with the description serve to explain examples of the present invention. 
         FIG. 1  shows an exemplary embodiment of an authentication system according to the present invention 
         FIG. 2  is a general flow diagram of an embodiment of the present invention 
         FIG. 3  is a detailed flow diagram of an exemplary embodiment of the present invention 
         FIG. 4  is a detailed flow diagram of a second embodiment of the present invention 
         FIG. 5  is an illustration of an individual&#39;s eye in the process of closing and/or opening 
         FIG. 6  shows a second exemplary embodiment of an authentication system according to the present invention 
     
    
    
     REFERENCE NUMERALS 
     
       
         
               
               
               
             
           
               
                   
                   
               
             
             
               
                   
                 100 
                 authentication requester 
               
               
                   
                 110 
                 authentication server 
               
               
                   
                 120 
                 Internet 
               
               
                   
                 130 
                 mobile device 
               
               
                   
                 140a 
                 hand 
               
               
                   
                 140b 
                 eye 
               
               
                   
                 140c 
                 face 
               
               
                   
                 200-416 
                 flow chart steps 
               
               
                   
                 501 
                 open eye 
               
               
                   
                 502 
                 partially open eye 
               
               
                   
                 503 
                 closed eye 
               
               
                   
                 600 
                 camera 
               
               
                   
                 602 
                 speaker 
               
               
                   
                   
               
             
          
         
       
     
     DETAILED DESCRIPTION 
     FIG.  1 —First Embodiment 
     The preferred embodiment of the invention is illustrated in  FIG. 1 . An Authentication Requester  100  such as an ecommerce or bank web site is connected to the Internet  120 . An Authentication Server  110  implementing the method described here is also connected to the Internet. The Internet is selected as a worst case transport network for the purposes of describing this embodiment, but more secure networks would be just as suitable. Requester  100  is connected to authentication server  110  over the Internet via a secure connection (e.g.—secure socket layer connection or other secure connections known to those familiar with the art). Both the requester  100  and server  110  are also able to securely connect to a camera-equipped, Internet capable mobile device  130  as required. This secure connection is also over the Internet  120 . The mobile device  130  is equipped with a speaker and an alphanumeric keypad, as well as a screen and camera of resolution typical of mobile phones currently for sale in the United States (e.g. one megapixel or better). This device need not be a mobile phone and could be a PDA, tablet computer, desktop computer, laptop computer, or any other electronic device that satisfies the characteristics outlined above. Lastly, the figure depicts three example biometric features of the user of the mobile device: the hand  140   a , eye  140   b  and face  140   c . This user is the subject requiring authentication by the requester  100 . The authentication will be performed by the server  110  in cooperation with the mobile device  130 . 
     FIGS.  2 ,  3 ,  5 —Operation 
     The inventive system performs replay-attack resistant biometric authentication with the general steps shown in the flow chart of  FIG. 2 . The preferred embodiment using iris pattern recognition is depicted in the flow chart of  FIG. 3 . The user  140  is attempting to access resources on a web site, such as financial or health related data. The website determines that a biometric authentication factor is required due to the sensitivity of the transaction, or because fraud is suspected, or for some other reason. At this point the website assumes the role of Authentication Requester  100  in  FIG. 1  and informs the user that biometric authentication will be required. 
     As represented in step  200  the requester  100  issues a request for authentication to the Authentication Server  110  over the Internet  120 . The request can be issued using any secure protocol known to those skilled in the art such as Hypertext Transfer Protocol Secure (HTTPS). At a minimum, this request message will contain a unique identifier (e.g.—name, account number, id number, phone number, etc.) for the user requiring authentication. However, the message could also include the user&#39;s known valid biometric data, mobile device identifier or requirements for the level of integrity demanded. The preferred embodiment would limit the request data to an account number in order to reduce the possibility of attacks attempted by submitting false data to the server  110 . 
     As represented by step  202 , upon receiving the request the Authentication Server  110  will use the submitted unique identifier to search its records for a record of that user. In the preferred embodiment the stored record will contain the user&#39;s mobile device phone number as well as the valid biometric data for that user. The server  110  will send a message to the user&#39;s mobile device  130  if that data is found. In the preferred embodiment this message will be an ordinary Short Message Service (SMS) message and software continuously running on the mobile device  130  will automatically display an alert to the user in response. The alert will indicate that a request for biometric authentication has been received. However, on mobile devices where a continuously running application would consume undue resources, the message could alternatively prompt the user to run the biometric authentication application themselves. Additionally, devices that are directly Internet addressable such as computers and smart phones can be contacted via their Internet Protocol (IP) address. 
     As represented by step  204  the application running on the mobile device  130  in response to the request in step  202  will establish a secure connection to the Authentication Server  110 . This application will activate the mobile device&#39;s camera and begin sending video frames to the server over that connection. In the preferred embodiment, data compression such as Lempel-Ziv-Welch (LZW) or other methods known to those skilled in the art will be used to encode the data and reduce bandwidth requirements for the mobile device link. Also, the number of image frames per second transmitted to the server and the resolution of those images will be set to a predetermined value to provide the maximum integrity possible within the limits of the device&#39;s available bandwidth. The server  110  will continuously run a biometric identification algorithm upon the incoming frames (an iris identification algorithm in the preferred embodiment, depicted in the flowchart of  FIG. 3 ) and will categorize the data stream as ‘valid’ as soon as extracted details match the details on file for the user in question. Conversely, the data stream will be categorized as invalid as soon as the extracted details do not match the details on file. The categorization of the stream as valid does not indicate successful authentication by itself. 
     After the biometric data stream has been categorized as ‘valid,’ the Authentication Server  110  will transmit random prompts to the mobile device as represented by step  206 . In the preferred embodiment the server  110  will use a Cryptographically Secure Random Number Generator (CSRNG) such as Blum Blum Shub or the Yarrow Algorithm to generate the random timing of these prompts in secret. A CSRNG is a random number generator that is effectively impossible for attackers to predict, although less secure random numbers may be adequate if the number of authentication attempts is limited. The delay periods need not be whole numbers, and will range from a single delay period for less demanding applications to an arbitrarily high number of delay periods for more critical applications as determined in advance. The prompts will be sent to the device in the form of trigger messages at the specified times, upon receipt of which the mobile device will prompt the user. In the preferred embodiment outlined in the flowchart of  FIG. 3  the system will play the sound of a human voice speaking the word ‘blink’ in the appropriate language. The user will blink as instructed when he or she hears this word. Alternatively, the words ‘open eye’ and ‘close eye’ can be used as instructions. 
     The continuous stream of image frames from the mobile device  130  to the Authentication Server  110  will now contain variations in the user&#39;s biometric data. In the preferred embodiment this will consist of images of the eye in various states of open, transition and closed. These states are depicted in  FIG. 5  as  501 ,  502 , and  503 , respectively. In step  208  the biometric authentication algorithm compares the detected time of these variations with the prompted times, taking into account the latency (delay) present in the network. The latency may be measured repeatedly using the standard ‘ping’ mechanism, using Network Time Protocol (NTP) or other methods known to those familiar with the art. For example, in the preferred embodiment the first blink prompt could be sent 2 seconds after the valid stream was established and the average round-trip network latency could be measured as 1 second. In that specific example the eye should be detected as closing and subsequently opening in the video frames arriving at the server 3 seconds after the valid stream was established. 
     Several opportunities exist to trade between the security and usability of the method at this point, best illustrated by considering the preferred embodiment (iris recognition). First, the tolerance in time between when the expected prompt should arrive and when it is observed can be adjusted. This would allow users more leeway in responding to the prompts and would subsequently reduce the likelihood of an accidental denial of authentication. However, in the preferred embodiment it would also increase the odds that a video of the real user&#39;s eye with random blinks (e.g.—captured from a previous authentication and replayed to the phone) would successfully authenticate. Second, methods such as that published by Bourennane et. al. in the Journal of Electronic Imaging 19(3), (July-September 2010) are able to make estimates of eyelid position. By monitoring the changing position of the eyelid this data can be used to ensure that a static picture of the subject&#39;s eye is not merely obscured by a user&#39;s hand at the prescribed intervals. This would come at the expense of additional processing requirements. Furthermore, since the algorithm must not be susceptible to replayed videos containing an extremely high number of blinks, a predetermined limit must be set on the number of unprompted blinks tolerated for a successful authentication. Most subjects blink uncontrollably to a certain degree, so again a tradeoff must be established here between integrity and usability; or more rigorously, the probability of detection and the probability of false alarm. Finally, a predetermined limit must be set on the allowed duration of a blink since the validity of the iris pattern data is not measurable during the time the eye is closed. 
     An additional benefit to using a central remotely located Authentication Server  110  is that actual biometric data streams can be stored by the server  110  and periodically audited to search for inventive attempts at subversion. Statistics from different data streams can also be compared automatically to search for identical, replayed data. Furthermore, improvements to the algorithm can be implemented in the server  110  so that all connecting devices immediately enjoy the benefits. 
     If the appropriate prompt responses are not detected in step  208 , the system will deny authentication as represented by step  214 , informing both the user and the Authentication Requester  100  of the fact and closing the session. In contrast, if the appropriate prompts are detected the system will then verify that the biometric data stream was valid for the entirety of the session, as represented by step  210 . As described earlier, the threshold criteria for validity are a predetermined but variable design parameter of the system. If these criteria are not met, the system denies authentication and proceeds to step  214  as just described. 
     If both the prompt appropriateness and data stream validity criteria are met then authentication is successful as represented by step  212 . The Authentication Server  110  informs both the user and the Authentication Requester  100  of this fact and terminates the connection to both the requester  100  and mobile device  130 . In the preferred embodiment the authentication confirmation message to the requester  100  will be digitally signed with a valid certificate in the manner known to those skilled in the art. Upon receipt of this confirmation the requester  100  can proceed with allowing the user to access the desired resources. 
     The primary embodiment of this general method is depicted in the detailed flowchart of  FIG. 3 , in which the chosen biometric feature is iris pattern. The flowchart starts after the mobile device  130  is contacted in step  202  from  FIG. 2 . At this point in step  300  the user is instructed to aim the mobile device  130  at the user&#39;s eye. The server validates that this iris pattern matches the user&#39;s known iris pattern in step  302 , and transmits the first prompt to blink at step  304 . After the user blinks in step  306 , the server  110  searches for the blink in the data during the allowable time window. If no blink is detected, authentication is denied in step  316 . If the blink is detected the server  110  checks the validity of the iris pattern immediately after the blink denying authentication if it is not valid. In step  312  the server  110  checks that the number of blinks is adequate to meet the confidence requirements of the system, issuing more blink prompts until the criteria is met. If the criteria are met then the system will progress to step  314 , approving authentication in the manner described in the discussion of step  212  above. 
     ADDITIONAL EMBODIMENTS 
     Additional embodiments are shown in  FIG. 4  and  FIG. 6 . In  FIG. 4  the system measures the position of a person&#39;s hand  140   a  in response to prompts rather than eyelid position. This embodiment uses the hand dimensions rather than the iris features as the basis for biometric authentication. Instead of prompted blinking, the system will prompt the user to extend and retract specific fingers at random time intervals. Aside from the replacement of the eye  140   b  with the hand, the system operates in analogous fashion. 
     In  FIG. 6  the Authentication Server  110  is integrated with the mobile device  130  into a single device without need for the Internet. In this embodiment the camera  600  and speaker  602  previously supplied by the mobile device  130  directly interface to the server. The advantage to this system is that it is self contained and could be installed in locations where Internet connections are undesirable or unavailable. One such example would be a door entry system in which a connection to the Internet is considered an undue security risk. In this embodiment the role of the Authentication Requester  100  is performed by user rather than a separate web site or other entity. Aside from these changes to the Internet  120 , mobile device  130 , and requester  100  components, the system operates in analogous fashion to the primary embodiment.