Biometric authentication has been attracting much attention because it is more user-friendly than other authentication methods such as password-based and token-based authentications. However, it intrinsically comprises problems of privacy and revocability. To address these issues, new techniques called cancelable biometrics have been proposed and their properties have been analyzed extensively. Nevertheless, only a few considered provable security, and provably secure schemes known to date had to sacrifice user-friendliness because users have to carry tokens so that they can securely access their secret keys. In this paper, we propose two cancelable biometric protocols each of which is provably secure and requires no secret key access of users. We use as an underlying component the Boneh-Goh-Nissim cryptosystem proposed in TCC 2005 and the Okamoto-Takashima cryptosystem proposed in Pairing 2008 in order to evaluate 2-DNF (disjunctive normal form) predicate on encrypted feature vectors. We define a security model in a semi-honest manner and give a formal proof which shows that our protocols are secure in that model. The revocation process of our protocols can be seen as a new way of utilizing the veiled property of the underlying cryptosystems, which may be of independent interest.

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Pairwise key establishment is a fundamental service provided in secure sensor networks. However, due to resource constraints, establishing pairwise keys is not a trivial task. Recently, a random key pre-distribution scheme and its improvements have been proposed. The scheme proposed by Du et al. uses deployment knowledge to improve the performance and security of sensor networks. However, this scheme assumes group-based deployment in which groups of nodes are deployed from horizontal grid points. This assumption limits applications of the scheme. Therefore, in this paper, we propose an advanced key pre-distribution scheme in which different keys are logically mapped to twodimensional positions, and the keys that are distributed to a node are determined by positions estimated using a node probability density function. The scheme can be applied to any deployment model provided the node probability density function has already been determined. Furthermore, simulation results show that our scheme achieves higher connectivity than Du et al.'s scheme.

SUMMARYIn order to establish encrypted communications in deployable sensor networks, it is essential that encryption keys be shared between nodes. However, the sharing of keys is not simple given the restricted resources of such devices. In recent years, several random key predistribution schemes have been proposed; in the scheme proposed by Du and colleagues, improved performance is achieved by using information regarding the deployment location when predistributing keys. However, this scheme suffers from the problem that it is possible to apply only for the so-called group deployment model whereby nodes are partitioned into groups and deployed from locations that are arranged systematically. In this paper we propose a random key predistribution scheme that can be applied to arbitrary deployment models by making use of probability distribution information regarding the deployment when the key predistribution is performed. In addition, we confirm from computational experiments that this method is able to construct networks that are more consolidated than those created by Du and colleagues' scheme.

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