A Security Supervision System for Hybrid Networks

The traditional way of protecting networks and applications with e.g., firewalls and encryption, is no longer sufficient to protect effectively emerging hybrid wired-cum-wireless networks including ad hoc networks. Intrusion detection mechanisms should be coupled with preventive measures so as to identify unauthorised abuses. To this end, we propose a novel Hybrid Distributed Security Operation Center (HDSOC) which collects logs that are generated by any application/service, layer of the protocol stack or resource (e.g., router), providing a global view of the supervised system based on which complex and distributed intrusions can be detected. Our HDSOC further (i) distributes its capabilities and (ii) provides extensive coordination capabilities for guarantying that both the networks and the HDSOC components do not constitute isolated entities largely unaware of each others

Let Opportunistic Crowdsensors Work Together for Resource-efficient, Quality-aware Observations

International audienceOpportunistic crowdsensing empowers citizens carrying hand-held devices to sense physical phenomena of common interest at a large and fine-grained scale without requiring the citizens' active involvement. However, the resulting uncontrolled collection and upload of the massive amount of contributed raw data incur significant resource consumption, from the end device to the server, as well as challenge the quality of the collected observations. This paper tackles both challenges raised by opportunistic crowdsensing, that is, enabling the resource-efficient gathering of relevant observations. To achieve so, we introduce the BeTogether middleware fostering context-aware, collaborative crowdsensing at the edge so that co-located crowdsensors operating in the same context, group together to share the work load in a cost- and quality-effective way. We evaluate the proposed solution using an implementation-driven evaluation that leverages a dataset embedding nearly 1 million entries contributed by 550 crowdsensors over a year. Results show that BeTogether increases the quality of the collected data while reducing the overall resource cost compared to the cloud-centric approach

Congenital tibial deficiencies: Treatment using the Ilizarov's external fixator

SummaryIntroductionCongenital longitudinal deficiency of the tibia is a rare and often syndromic anomaly. Amputation is usually the preferred treatment option in complete absence of the tibia; however, a conservative management might be implemented in partial forms or in case of amputation refusal. Our experience with the Ilizarov fixator, convinced us this device was the best suited for progressive correction of lower limbs length discrepancies and articular or bone angular limb deformities (ALD). The aim of this study is to highlight the interest of the Ilizarov fixator in the multistage conservative treatment of congenital tibial deficiencies.Material and methodsA retrospective study was conducted in nine patients suffering from Type I or II congenital tibial deficiencies (Jones) and sequentially managed using the Ilizarov technique. The functional outcome after treatment completion was then clinically assessed.ResultsThe different stages of correction were recorded for each individual patient. Patients were assessed at a mean follow-up of 18,3 years (4–32 years). The mean maximum knee flexion was 35° (0°–90°) in type I deficiencies and 118° (90°–140°) in type II deficiencies. One patient underwent amputation and a bilateral knee arthrodesis was performed in another case.DiscussionFew series in the literature report a comparable length of follow-up period in the conservative management of severe congenital tibial deficiencies. In our study, the Ilizarov fixator provided satisfactory progressive corrections of severe congenital tibial deficiencies.Level of EvidenceLevel IV therapeutic retrospective study

IAM - Interpolation and Aggregation on the Move: Collaborative Crowdsensing for Spatio-temporal Phenomena

International audienceCrowdsensing allows citizens to contribute to the monitoring of their living environment using the sensors embedded in their mobile devices, e.g., smartphones. However, crowdsensing at scale involves significant communication, computation, and financial costs due to the dependence on cloud infrastructures for the analysis (e.g., interpolation and aggregation) of spatio-temporal data. This limits the adoption of crowdsensing by activists although sorely needed to inform our knowledge of the environment. As an alternative to the centralized analysis of crowdsensed observations, this paper introduces a fully distributed interpolation-mediated aggregation approach running on smartphones. To achieve so efficiently, we model the interpolation as a distributed tensor completion problem, and we introduce a lightweight aggregation strategy that anticipates the likelihood of future encounters according to the quality of the interpolation. Our approach thus shifts the centralized postprocessing of crowdsensed data to distributed pre-processing on the move, based on opportunistic encounters of crowdsensors through state-of-the-art D2D networking. The evaluation using a dataset of quantitative environmental measurements collected from 550 crowdsensors over 1 year shows that our solution significantly reduces-and may even eliminate-the dependence on the cloud infrastructure, while it incurs a limited resource cost on end devices. Meanwhile, the overall data accuracy remains comparable to that of the centralized approach

User-centric Context Inference for Mobile Crowdsensing

International audienceMobile crowdsensing is a powerful mechanism to aggregate hyper-local knowledge about the environment. Indeed, users may contribute valuable observations across time and space using the sensors embedded in their smartphones. However, the relevance of the provided measurements depends on the adequacy of the sensing context with respect to the phenomena that are analyzed. This paper concentrates more specifically on assessing the sensing context when gathering observations about the physical environment beyond its geographical position in the Euclidean space, i.e., whether the phone is in-/out-pocket, in-/out-door and on-/under-ground. We introduce an online learning approach to the local inference of the sensing context so as to overcome the disparity of the classification performance due to the heterogeneity of the sensing devices as well as the diversity of user behavior and novel usage scenarios. Our approach specifically features a hierarchical algorithm for inference that requires few opportunistic feedbacks from the user, while increasing the accuracy of the context inference per user

Let Opportunistic Crowdsensors Work Together for Resource-efficient, Quality-aware Observations

International audienceOpportunistic crowdsensing empowers citizens carrying hand-held devices to sense physical phenomena of common interest at a large and fine-grained scale without requiring the citizens' active involvement. However, the resulting uncontrolled collection and upload of the massive amount of contributed raw data incur significant resource consumption, from the end device to the server, as well as challenge the quality of the collected observations. This paper tackles both challenges raised by opportunistic crowdsensing, that is, enabling the resource-efficient gathering of relevant observations. To achieve so, we introduce the BeTogether middleware fostering context-aware, collaborative crowdsensing at the edge so that co-located crowdsensors operating in the same context, group together to share the work load in a cost- and quality-effective way. We evaluate the proposed solution using an implementation-driven evaluation that leverages a dataset embedding nearly 1 million entries contributed by 550 crowdsensors over a year. Results show that BeTogether increases the quality of the collected data while reducing the overall resource cost compared to the cloud-centric approach

Multi-Sensor Calibration Planning in IoT-Enabled Smart Spaces

International audienc

Secondary structure of rhBMP-2 in a protective biopolymeric carrier material

Efficient delivery of growth factors is one of the great challenges of tissue engineering. Polyelectrolyte multilayer films (PEM) made of biopolymers have recently emerged as an interesting carrier for delivering recombinant human bone morphogenetic protein 2 (rhBMP-2 noted here BMP-2) to cells in a matrix-bound manner. We recently showed that PEM made of poly(l-lysine) and hyaluronan (PLL/HA) can retain high and tunable quantities of BMP-2 and can deliver it to cells to induce their differentiation in osteoblasts. Here, we investigate quantitatively by Fourier transform infrared spectroscopy (FTIR) the secondary structure of BMP-2 in solution as well as trapped in a biopolymeric thin film. We reveal that the major structural elements of BMP-2 in solution are intramolecular β-sheets and unordered structures as well as α-helices. Furthermore, we studied the secondary structure of rhBMP-2 trapped in hydrated films and in dry films since drying is an important step for future applications of these bioactive films onto orthopedic biomaterials. We demonstrate that the structural elements were preserved when BMP-2 was trapped in the biopolymeric film in hydrated conditions and, to a lesser extent, in dry state. Importantly, its bioactivity was maintained after drying of the film. Our results appear highly promising for future applications of these films as coatings of biomedical materials, to deliver bioactive proteins while preserving their bioactivity upon storage in dry state.This work was supported by the French Ministry of Research through an ANR-EmergenceBIO grant (ANR-09-EBIO-012-01), by the European Commission (FP7 program) via a European Research Council starting grant (BIOMIM, GA 259370), and by GRAVIT (081012_FIBIOS). C.P. is grafetul to IUF for financial support

A spontaneous ad hoc network to share www access

In this paper, we propose a secure spontaneous ad-hoc network, based on direct peer-to-peer interaction, to grant a quick, easy, and secure access to the users to surf the Web. The paper shows the description of our proposal, the procedure of the nodes involved in the system, the security algorithms implemented, and the designed messages. We have taken into account the security and its performance. Although some people have defined and described the main features of spontaneous ad-hoc networks, nobody has published any design and simulation until today. Spontaneous networking will enable a more natural form of wireless computing when people physically meet in the real world. We also validate the success of our proposal through several simulations and comparisons with a regular architecture, taking into account the optimization of the resources of the devices. Finally, we compare our proposal with other caching techniques published in the related literature. The proposal has been developed with the main objective of improving the communication and integration between different study centers of low-resource communities. That is, it lets communicate spontaneous networks, which are working collaboratively and which have been created on different physical places.Authors want to give thanks to the anonymous reviewers for their valuable suggestions, useful comments, and proofreading of this paper. This work was partially supported by the Ministerio de Educacion y Ciencia, Spain, under Grant no. TIN2008-06441-C02-01, and by the "Ayudas complementarias para proyectos de I+D para grupos de calidad de la Generalitat Valenciana" (ACOMP/2010/005).Lacuesta Gilaberte, R.; Lloret, J.; García Pineda, M.; Peñalver Herrero, ML. (2010). A spontaneous ad hoc network to share www access. 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