A Decoupled 3D Facial Shape Model by Adversarial Training

Data-driven generative 3D face models are used to compactly encode facial shape data into meaningful parametric representations. A desirable property of these models is their ability to effectively decouple natural sources of variation, in particular identity and expression. While factorized representations have been proposed for that purpose, they are still limited in the variability they can capture and may present modeling artifacts when applied to tasks such as expression transfer. In this work, we explore a new direction with Generative Adversarial Networks and show that they contribute to better face modeling performances, especially in decoupling natural factors, while also achieving more diverse samples. To train the model we introduce a novel architecture that combines a 3D generator with a 2D discriminator that leverages conventional CNNs, where the two components are bridged by a geometry mapping layer. We further present a training scheme, based on auxiliary classifiers, to explicitly disentangle identity and expression attributes. Through quantitative and qualitative results on standard face datasets, we illustrate the benefits of our model and demonstrate that it outperforms competing state of the art methods in terms of decoupling and diversity.Comment: camera-ready version for ICCV'1

Trust-based security for the OLSR routing protocol

International audienceThe trust is always present implicitly in the protocols based on cooperation, in particular, between the entities involved in routing operations in Ad hoc networks. Indeed, as the wireless range of such nodes is limited, the nodes mutually cooperate with their neighbors in order to extend the remote nodes and the entire network. In our work, we are interested by trust as security solution for OLSR protocol. This approach fits particularly with characteristics of ad hoc networks. Moreover, the explicit trust management allows entities to reason with and about trust, and to take decisions regarding other entities. In this paper, we detail the techniques and the contributions in trust-based security in OLSR. We present trust-based analysis of the OLSR protocol using trust specification language, and we show how trust-based reasoning can allow each node to evaluate the behavior of the other nodes. After the detection of misbehaving nodes, we propose solutions of prevention and countermeasures to resolve the situations of inconsistency, and counter the malicious nodes. We demonstrate the effectiveness of our solution taking different simulated attacks scenarios. Our approach brings few modifications and is still compatible with the bare OLSR

On the threshold energization of radiation belt electrons by double layers

Using a Hamiltonian approach, we quantify the energization threshold of electrons interacting with radiation belts' double layers discovered by Mozer et al. (2013). We find that double layers with electric field amplitude E0 ranging between 10 and 100 mV/m and spatial scales of the order of few Debye lengths are very efficient in energizing electrons with initial velocities v∥ ≤ vth to 1 keV levels but are unable to energize electrons with E ≥ 100 keV. Our results indicate that the localized electric field associated with the double layers are unlikely to generate a seed population of 100 keV necessary for a plethora of relativistic acceleration mechanisms and additional transport to higher energetic levels.Peer reviewe

MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles

Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.N/A

Multipath optimized link state routing for mobile ad hoc networks

International audienceMultipath routing protocols for Mobile Ad hoc NETwork (MANET) address the problem of scalability, security (confidentiality and integrity), lifetime of networks, instability of wireless transmissions, and their adaptation to applications. Our protocol, called MP-OLSR (MultiPath OLSR), is a multipath routing protocol based on OLSR. The Multipath Dijkstra Algorithm is proposed to obtain multiple paths. The algorithm gains great flexibility and extensibility by employing different link metrics and cost functions. In addition, route recovery and loop detection are implemented in MP-OLSR in order to improve quality of service regarding OLSR. The backward compatibility with OLSR based on IP source routing is also studied. Simulation based on Qualnet simulator is performed in different scenarios. A testbed is also set up to validate the protocol in real world. The results reveal that MP-OLSR is suitable for mobile, large and dense networks with large traffic, and could satisfy critical multimedia applications with high on time constraints

Substructure method for an assembly of structures invariant in one direction

International audienceThis study deals with the modeling by finite elements of an elastomeric composite structure. The main difficulties lie in the heterogeneity of the piece and in the geometrical non-linearity due to the centrifugal forces. We use the combination of two different methods of level sub-structuring. The first one is a multi-level sub-structuring method and the second is a more classical sub-structuring. After computation, the complete solution in displacement, the complete stress field and the global dumping of the structure (by an energetic method) are obtained

Street trading in the shadows of the Arab Spring

This paper examines the Arab revolutions of 2011 in Tunisia and Egypt, and their impact on street traders in Tunis and Cairo. Drawing on the literatures on urban conflict and resilience, the paper argues that the authoritarian regimes that the revolutions deposed left a vacuum in governance in which street traders found it hard to profit from the idealism and opportunism of an emerging new order. Despite being hindered by their lack of organization and voice, and disruption to their trade during the revolutions, street traders displayed resilience through small-scale adaptations to their trade and absorbed newcomers into the sector in the face of political conflict