- Email: [email protected]
DSV — questions remain…
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FEATURE
DSV – questions remain... In an age of e- and m-commerce and digital connectivity, the need to capture signatures securely and to verify the identity of people is becoming increasingly important. However questions surrounding dynamic signature verification technology still remain. Dynamic signature verification (DSV) is the capture and verification of a signature to confirm the identity of a user. The technology offers a number of advantages over other biometrics. People are familiar with writing their signatures to authorise transactions, and do not see it as a threatening technology. It can also be very inexpensive to implement. The primary reason that interest in DSV is growing is not because of algorithm improvements, but because it is becoming increasingly easy and possible to capture signatures, not only from special tablets or pens, but also from PDAs, computer displays with touch screens and the latest laptops. This is significant as it can make it possible for DSV to be implemented as a software only solution. Use of such devices for electronic capture of signatures is now becoming widespread in applications such as signing to acknowledge receipt of a parcel delivery. (Note, however, that simple signature capture systems do not record or compare dynamic features of signatures.) The significant difficulties and frustration which users have with passwords and PINs today, combined with the growth of eand m-commerce, remote working, remote banking, together with the growth of digital connectivity through broadband and wireless networks is creating an ever-greater need for innovative solutions for authentication of an individual. To date there have not been major trials of DSV systems that test performance amongst different sections of population, age groups, languages, etc. With many other biometric methods such as fingerprint, facial or iris recognition, large databases of sample images have been constructed enabling comparison
Figure 1. These two signatures were identified as coming from the same person by a DSV algorithm.
Biometric Technology Today • November/December 2003
algorithms to be tested thoroughly offline. Therefore, an independent dynamic signature technology benchmark similar to FVC1 for fingerprint is still awaited.2 Some questions remain open. How unique are people’s signatures? What is the chance that people with the same name might have similar signatures? Does this put people with common names at a disadvantage compared to those with unusual names? For example, in one major UK enterprise alone, there are currently 285 people called J. Smith. Current DSV technologies can have problems with people who have either very long or very short signatures. With short signatures, there is insufficient information to be confident in the uniqueness of the signature. However, long signatures can be too large for some capture devices, and algorithms can find it difficult to locate consistently replicable features in such signatures. What is the distribution of signatures over the population in terms of length and complexity? Although DSV algorithms offer many advantages over a visual comparison of signatures, they may be less sensitive to the shape of a signature. A commercial DSV algorithm interpreted the two signatures shown in Figure 1 as coming from the same person, where a human being would classify them as being different. In some cases it may be desirable to be able to extract the original signatures from the user template. This can be useful for legal reasons in situations where the ordinary static image of a person’s signature is needed, or to resolve disputes about verification. The above example shows that DSV might not always be able to resolve such disputes in a court of law. How do DSV algorithms compare with handwriting experts in analysing signatures? DSV can be used alongside digital signatures, for which there are already clear legal regulations in many countries and in the European Union. Some of the dynamic components of a signature which are commonly taken into consideration are the total time taken to sign and the speed of strokes. These tend to differ
accordingly to what the user is signing for. If it is a job application, an individual may sign more slowly than if it is a phone bill. Furthermore, a person’s signature naturally varies according to mood, posture and the physical characteristics of the pen. Thus, ideally, enrolment should involve capturing signatures over a long time frame in order to allow for these variations. However, this is difficult and costly in practice. Also, the signature template can be updated every time a matching signature is recorded to accommodate long-term changes to signatures. How does this affect the strength of DSV as a security mechanism? How much do signatures change over a lifetime? This may not have such an effect in the context of the same application, but it might have consequences if the same enrolment data is being used across multiple applications. Can algorithms successfully distinguish between someone signing carefully, and a forgery? In some applications, a user could sign a phrase which is not their usual signature, thus enabling users to be authenticated without revealing their signature. How consistently and distinctively can users write text which is not their usual signature? How many different signatures can users remember? In conclusion, there are clear technology and application drivers for the use of DSV. Over the next few years, we expect to see further advances in signature capture devices, especially the move towards paperlike flexible displays that will improve the potential for signing electronically. These advances, together with improvements in analysis algorithms, and the falling cost of computer processing will strengthen the case for the use of DSV. Whilst there are encouraging signs about the adoption of the technology, further research is still needed.
References 1. http://bias.csr.unibo.it/fvc2002. 2. Marek Rejman-Greene et al, Roadmap for Biometrics in Europe to 2010, http://www.eubiometricforum.com. This article was contributed by Luann Rragami, Maurice Gifford and Nicholas Edwards at BT Exact. For further information email: [email protected]
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22/10/2003
15:12
Page 7
FEATURE
DSV – questions remain... In an age of e- and m-commerce and digital connectivity, the need to capture signatures securely and to verify the identity of people is becoming increasingly important. However questions surrounding dynamic signature verification technology still remain. Dynamic signature verification (DSV) is the capture and verification of a signature to confirm the identity of a user. The technology offers a number of advantages over other biometrics. People are familiar with writing their signatures to authorise transactions, and do not see it as a threatening technology. It can also be very inexpensive to implement. The primary reason that interest in DSV is growing is not because of algorithm improvements, but because it is becoming increasingly easy and possible to capture signatures, not only from special tablets or pens, but also from PDAs, computer displays with touch screens and the latest laptops. This is significant as it can make it possible for DSV to be implemented as a software only solution. Use of such devices for electronic capture of signatures is now becoming widespread in applications such as signing to acknowledge receipt of a parcel delivery. (Note, however, that simple signature capture systems do not record or compare dynamic features of signatures.) The significant difficulties and frustration which users have with passwords and PINs today, combined with the growth of eand m-commerce, remote working, remote banking, together with the growth of digital connectivity through broadband and wireless networks is creating an ever-greater need for innovative solutions for authentication of an individual. To date there have not been major trials of DSV systems that test performance amongst different sections of population, age groups, languages, etc. With many other biometric methods such as fingerprint, facial or iris recognition, large databases of sample images have been constructed enabling comparison
Figure 1. These two signatures were identified as coming from the same person by a DSV algorithm.
Biometric Technology Today • November/December 2003
algorithms to be tested thoroughly offline. Therefore, an independent dynamic signature technology benchmark similar to FVC1 for fingerprint is still awaited.2 Some questions remain open. How unique are people’s signatures? What is the chance that people with the same name might have similar signatures? Does this put people with common names at a disadvantage compared to those with unusual names? For example, in one major UK enterprise alone, there are currently 285 people called J. Smith. Current DSV technologies can have problems with people who have either very long or very short signatures. With short signatures, there is insufficient information to be confident in the uniqueness of the signature. However, long signatures can be too large for some capture devices, and algorithms can find it difficult to locate consistently replicable features in such signatures. What is the distribution of signatures over the population in terms of length and complexity? Although DSV algorithms offer many advantages over a visual comparison of signatures, they may be less sensitive to the shape of a signature. A commercial DSV algorithm interpreted the two signatures shown in Figure 1 as coming from the same person, where a human being would classify them as being different. In some cases it may be desirable to be able to extract the original signatures from the user template. This can be useful for legal reasons in situations where the ordinary static image of a person’s signature is needed, or to resolve disputes about verification. The above example shows that DSV might not always be able to resolve such disputes in a court of law. How do DSV algorithms compare with handwriting experts in analysing signatures? DSV can be used alongside digital signatures, for which there are already clear legal regulations in many countries and in the European Union. Some of the dynamic components of a signature which are commonly taken into consideration are the total time taken to sign and the speed of strokes. These tend to differ
accordingly to what the user is signing for. If it is a job application, an individual may sign more slowly than if it is a phone bill. Furthermore, a person’s signature naturally varies according to mood, posture and the physical characteristics of the pen. Thus, ideally, enrolment should involve capturing signatures over a long time frame in order to allow for these variations. However, this is difficult and costly in practice. Also, the signature template can be updated every time a matching signature is recorded to accommodate long-term changes to signatures. How does this affect the strength of DSV as a security mechanism? How much do signatures change over a lifetime? This may not have such an effect in the context of the same application, but it might have consequences if the same enrolment data is being used across multiple applications. Can algorithms successfully distinguish between someone signing carefully, and a forgery? In some applications, a user could sign a phrase which is not their usual signature, thus enabling users to be authenticated without revealing their signature. How consistently and distinctively can users write text which is not their usual signature? How many different signatures can users remember? In conclusion, there are clear technology and application drivers for the use of DSV. Over the next few years, we expect to see further advances in signature capture devices, especially the move towards paperlike flexible displays that will improve the potential for signing electronically. These advances, together with improvements in analysis algorithms, and the falling cost of computer processing will strengthen the case for the use of DSV. Whilst there are encouraging signs about the adoption of the technology, further research is still needed.
References 1. http://bias.csr.unibo.it/fvc2002. 2. Marek Rejman-Greene et al, Roadmap for Biometrics in Europe to 2010, http://www.eubiometricforum.com. This article was contributed by Luann Rragami, Maurice Gifford and Nicholas Edwards at BT Exact. For further information email: [email protected]
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