This paper presents a new method to evaluate time stamping schemes from three viewpoints: integrity of a time stamp, cost of issuing and verifying a time stamp and availability of the schemes. The main advantage of the proposed evaluation method is to clarify whether or not a certain scheme is optimal under certain prioritized requirements. Therefore, the proposed method can help potential users of time stamping services select an appropriate one which meets their prioritized requirements. In this paper, we explain the basic idea of the evaluation method and show how to use it by applying it to seven existing schemes.

Time stamping is a technique used to prove the existence of certain digital data prior to a specific point in time. With the recent expansion of electronic commerce, it has been widely recognized as an important technique for ensuring the integrity of digital data for a long time period. Recently, various time stamping schemes have been proposed. However, a framework for evaluating their security and cost has not yet been established. Therefore, it has been difficult for users and system designers to select appropriate time stamping schemes. This paper presents a new framework for evaluating the security and cost of time stamping schemes. Our framework classifies time stamping schemes into 108 categories and clarifies their characteristics with regard to security and cost. By applying our framework to a certain scheme, we can easily evaluate its security and cost without discussing details of its specification. In this paper, we explain the basic idea of our framework and show how to use it by applying it to four existing schemes: Digital Notary/SecureSeal, PKITS, TIMESEC and Cuculus.

This paper will propose a wolf attack probability (WAP) as a new measure for evaluating security of biometric authentication systems. The wolf attack is an attempt to impersonate a victim by feeding "wolves" into the system to be attacked. The "wolf" means an input value which can be falsely accepted as a match with multiple templates. WAP is defined as a maximum success probability of the wolf attack with one wolf sample. In this paper, we give a rigorous definition of the new security measure which gives strength estimation of an individual biometric authentication system against impersonation attacks. We show that if one reestimates using our WAP measure, a typical fingerprint algorithm turns out to be much weaker than theoretically estimated by Ratha et al. Moreover, we apply the wolf attack to a finger-vein-pattern based algorithm. Surprisingly, we show that there exists an extremely strong wolf which falsely matches all templates for any threshold value.