Clustering validity measures aim to evaluate the goodness of clustering results in order to find the best partition. Results are obtained by varying the input parameters values. However, sometimes, the values generated by these measures are very close and the choice of the optimal value associated to the best partition may be meaningless. In this paper, we propose a new concept called hybrid strategy to resolve this problem. This concept is based on the use of two measures. The first measure aims to analyse the goodness of each partition obtained with different values of input parameters. The use of the second measure permits to select the best partition between those having good but very close values of the first measure. To illustrate this strategy, we propose a new hybrid measure ---called "HS-measure"--- based on Homogeneity degree and Silhouette coefficient. The performance of our measure is then tested on road traffic data set.

Clustering is an active research topic in data mining and different methods have been proposed in the literature. Most of these methods are based on the use of a distance measure defined either on numerical attributes or on categorical attributes. However, in fields such as road traffic and medicine, datasets are composed of numerical and categorical attributes. Recently, there have been several proposals to develop clustering methods that support mixed attributes. There are three basic categories of clustering methods: partitional methods, hierarchical methods and density-based methods. This paper proposes an extension of partitional clustering methods devoted to mixed attributes. The proposed extension looks to create several partitions by using numerical attributes-based clustering methods and then chooses the one that maximizes a measure---called ``homogeneity degree"---of these partitions according to categorical attributes.

Timestamping [1] is a cryptographic technique for adding a reliable date to a document in order to prove its existence at a given time. Several solutions of timestamping exist. They are all based on cryptographic techniques as digital signatures and hash functions. However, with the increase of computing power and the evolution of cryptanalysis methods, cryptography becomes more and more the target of criticism. That's why we need new directions and orientations for timestamping techniques. One of these directions was introduced in [2] and dealt with non interactive timestamping solutions in the Bounded Storage Model. In the Bounded Storage Model, we make the hypothesis that user's storage capacity is bounded but user's computing power is unlimited. In this paper, we first present the existing timestamping systems. Then we introduce the Bounded Storage Model. Finally, we present a new timestamping schema that we have conceived in the bounded storage model.

Time-stamping is a technique used to prove the existence of a digital document prior to a specific point in time. Today, implemented schemes rely on a centralized server model that has to be trusted. We point out the drawbacks of these schemes, showing that the unique serveur represent a weak point for the system. We propose an alternative scheme which is based on a network of servers managed by administratively independent entities. This scheme appears to be a trusted and reliable distributed time-stamping scheme.