The Internet of Things (IoT) vision is a groundbreaking networking evolution that connects all things that were not meant to be connected to the Internet. Thus, identification technologies and Internet-enabled wireless sensor nodes will be incorporated in homes, cities, vehicles, watches, etc. making them uniquely identified and able to process and communicate information via Internet. Hence, the emergence of the Internet of Things paradigm will bring a lot of smartness to our daily life and will improve the way people monitor their goods, expenses, environment and health status. The smart connected things in the IoT interact with each other and/or with the regular Internet hosts according to two communications styles: Thing-to-Thing(s) (T2T) and Human-to-Thing (H2T). Enabling security for such communications is a real issue especially in H2T interactions. This is mainly due to scarce resources of the connected objects and the asymmetric nature of the communications between those smart things and the ordinary Internet hosts. In this paper we address this problematic and we propose an asymmetric security model that mitigates H2T communication heterogeneities and provides reasonable security costs.

In this paper, we show that the asymptotic expansion of a double Laplace-type integral with a non-stationary minimum point, located on the boundary of the domain of integration, is governed by the order of contact between the boundary curve and the level curve of the phase through the minimum point. This achievement will enable us to construct complete asymptotic expansions in more general settings. Especially, the problem will be completely solved if the phase and the boundary curve of the domain of integration are analytic near the minimum point.

A detailed biostratigraphic study of four sections (El Kantara, Menaa, Tighanimine and El Gaâga) in the Campanian–Maastrichtian of the Aures Basin in Algeria allows the identification of 109 ostracod species belonging to 50 genera. From a biochronostratigraphic point of view, none of the identified ostracod assemblages are typically restricted to the Campanian or to the Maastrichtian, but rather characterize a range covering the Campanian–Maastrichtian. As regards the paleobiogeography, the presence of species in common between Algeria and other countries or regions enables us to compile four maps showing the distribution of two provinces that developed during the Santonian-Paleocene, i) the South-West and South Tethyan Margins Province, including North Africa, the Middle East and Arabian Peninsula, and ii) the East Atlantic Margin Province, bordering West and Central-West Africa. We can also recognize relationships between the different regions making up these provinces, which remained under more or less arid, subtropical to tropical climates, with ostracods migrating according to the directions of ocean currents during the Late Cretaceous. The dispersal of the ostracods reflects marine communication between these provinces and India, the southern USA and Jamaica, Brazil and Europe.

  This paper aims to address the assessment the similarity between documents or pieces of documents. For this purpose we have developed CASISS (CAlculation of SImilarity of Semi-Structured documents) method to quantify how two given texts are similar. The method can be employed in wide area of applications including content reuse detection which is a hot and challenging topic. It can be also used to increase the accuracy of the information retrieval process by taking into account not only the presence of query terms in the given document (Content Only search — CO) but also the topology (position continuity) of these terms (based on Content And Structure Search — CAS). Tracking the origin of the information in social media, copy right management, plagiarism detection, social media mining and monitoring, digital forensic are among other applications require tools such as CASISS to measure, with a high accuracy, the content overlap between two documents. CASISS identify elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of elements descriptors, which characterize the content of the elements.