Multivariate High-Order Attacks of Shuffled Tables Recomputation

Masking schemes based on tables recomputation are classical countermeasures against high-order side-channel attacks. Still, they are known to be attackable at order d in the case the masking involves d shares. In this work, we mathematically show that an attack of order strictly greater than d can be more successful than an attack at order d. To do so, we leverage the idea presented by Tunstall, Whitnall and Oswald at FSE 2013: We exhibit attacks which exploit the multiple leakages linked to one mask during the recomputation of tables. Specifically, regarding first-order table recomputation, improved by a shuffled execution, we show that there is a window of opportunity, in terms of noise variance, where a novel highly multivariate third-order attack is more efficient than a classical bivariate second-order attack. Moreover, we show on the example of the high-order secure table computation presented by Coron at EUROCRYPT 2014 that the window of opportunity enlarges linearly with the security order d. These results extend that of the CHES ’15 eponymous paper. Here, we also investigate the case of degree one leakage models and formally show that the Hamming weight model is the less favorable to the attacker. Eventually, we validate our attack on a real ATMEL smartcard.     

0D/2D Heterostructures Vertical Single Electron Transistor

Mixed-dimensional heterostructures formed by the stacking of 2D materials with nanostructures of distinct dimensionality constitute a new class of nanomaterials that offers multifunctionality that goes beyond those of single dimensional systems. An unexplored architecture of single electron transistor (SET) is developed that employs heterostructures made of nanoclusters (0D) grown on a 2D molybdenum disulfide (MoS₂) channel. Combining the large Coulomb energy of the nanoclusters with the electronic capabilities of the 2D layer, the concept of 0D–2D vertical SET is unveiled. The MoS₂ underneath serves both as a charge tunable channel interconnecting the electrode, and as bottom electrode for each v-SET cell. In addition, its atomic thickness makes it thinner than the Debye screening length, providing electric field transparency functionality that allows for an efficient electric back gate control of the nanoclusters charge state. The Coulomb diamond pattern characteristics of SET are reported, with specific doping dependent nonlinear features arising from the 0D/2D geometry that are elucidated by theoretical modeling. These results hold promise for multifunctional single electron device taking advantage of the versatility of the 2D materials library, with as example envisioned spintronics applications while coupling quantum dots to magnetic 2D material, or to ferroelectric layers for neuromorphic devices.     

Modeling and implementation of 5G edge caching over satellite

The fifth‐generation (5G) wireless networks have to deal with the high data rate and stringent latency requirements due to the massive invasion of connected devices and data‐hungry applications. Edge caching is a promising technique to overcome these challenges by prefetching the content closer to the end users at the edge node's local storage. In this paper, we analyze the performance of edge caching 5G networks with the aid of satellite communication systems. First, we investigate the satellite‐aided edge caching systems in two promising use cases: (a) in dense urban areas and (b) in sparsely populated regions, eg, rural areas. Second, we study the effectiveness of satellite systems via the proposed satellite‐aided caching algorithm, which can be used in three configurations: (a) mono‐beam satellite, (b) multi‐beam satellite, and (c) hybrid mode. Third, the proposed caching algorithm is evaluated by using both empirical Zipf‐distribution data and the more realistic Movielens dataset. Last but not least, the proposed caching scheme is implemented and tested by our developed demonstrators which allow real‐time analysis of the cache hit ratio and cost analysis.     

Minimising work overload in mixed-model assembly lines with different types of operators: a case study from the truck industry

This paper considers the problem of sequencing mixed-model assembly lines (MMALs). Our goal is to determine the sequence of products to minimise work overload. This problem is known as the MMAL sequencing problem with work overload minimisation: we explicitly use task operation times to find the product sequence. This paper is based on an industrial case study of a truck assembly line. In this industrial context, as a reaction to work overloads, operators at the workstations finish their tasks before the product reaches the next workstation, but at the expense of fatigue. Furthermore, there are different types of operators, each with different task responsibilities. The originality of this work is to model this new way of reacting against work overloads, to integrate three operator types in the sequencing model and to apply the developed methods in a real industrial context. To solve this problem, we propose three meta-heuristic procedures: genetic algorithm, simulated annealing and a combination of these two meta-heuristics. All the methods proposed are tested on industrial data and compared to the solutions obtained using a mixed-integer linear programme. The results show that the proposed methods considerably improve the results of the current procedure used in the case study.     

Enforcing logical delays in DNA computing systems

DNA computing has the potential to create powerful devices, but, in the context of well-mixed systems, sequentiality of operations is hard to achieve. To enforce such sequentiality, we propose a generic delay gate that can be interfaced with virtually any DNA system. Since it is system-independent, our delay gate can be used as an off-the-shelf library to accelerate the design of increasingly complex systems. Additionally, we checked the feasibility of our design by testing various in vitro implementations. We also present a theoretical proof of concept of its applicability by using it to complement an existing DNA module library, the DNA toolbox, to design new systems.     

Sparsity Driven People Localization with a Heterogeneous Network of Cameras

This paper addresses the problem of localizing people in low and high density crowds with a network of heterogeneous cameras. The problem is recast as a linear inverse problem. It relies on deducing the discretized occupancy vector of people on the ground, from the noisy binary silhouettes observed as foreground pixels in each camera. This inverse problem is regularized by imposing a sparse occupancy vector, i.e., made of few non-zero elements, while a particular dictionary of silhouettes linearly maps these non-empty grid locations to the multiple silhouettes viewed by the cameras network. The proposed framework is (i) generic to any scene of people, i.e., people are located in low and high density crowds, (ii) scalable to any number of cameras and already working with a single camera, (iii) unconstrained by the scene surface to be monitored, and (iv) versatile with respect to the camera??s geometry, e.g., planar or omnidirectional. Qualitative and quantitative results are presented on the APIDIS and the PETS 2009 Benchmark datasets. The proposed algorithm successfully detects people occluding each other given severely degraded extracted features, while outperforming state-of-the-art people localization techniques.     

A multi-class approximation technique for the analysis of kanban-like control systems

Analytical methods have been proposed in the literature for performance evaluation of kanban control systems. Among them, the method presented by Di Mascolo and colleagues appears to be of special interest since it can handle manufacturing stages consisting of any number of machines and it is fairly accurate. This paper presents a new way of deriving the analytical method presented by Di Mascolo et al. The approach is to see the queueing network of the kanban control system as a multiclass queueing network in which each kanban loop is represented by a class of customers. This allows one to use the general technique proposed in Baynat and Dallery for analysing multiclass queueing network using product-form approximation methods. In terms of equations, the new method is equivalent to that previously presented. However, the computational algorithm is much more efficient since it avoids the two levels of iterations involved in the original algorithm. Another major advantage of the new method over that originally proposed is that it provides a general framework for the analysis of more general kanban systems. Indeed, it is shown in this paper how this approach can easily be extended in order to handle kanban systems with multiple consumers and multiple suppliers, kanban-controlled assembly systems and generalized kanban systems.     

Robust assignment of customer orders with uncertain configurations in a production network for aircraft manufacturing

Production of multi-variant products in a network requires the assignment of customer orders to locations and periods. This is a highly complex planning task, as requirements of procurement, production, distribution, and sales have to be considered. Providing customers with the flexibility of configuring their ordered products after order assignment further increases the complexity of the planning task by taking uncertainty into account. Therefore, a robust optimisation model, using scenarios representing potential customer-specific order configurations, is introduced. By providing enough flexibility to handle maximum work overload caused by the potential order configurations at locations, a robust assignment of orders can be guaranteed in order to avoid undesirable situations causing delays and additional costs. Therefore, the mid-term adjustments of the flexibility limits are enabled by the changeability of workforce supply by making use of external workers. An industrial application of the model in manufacturing of the Airbus A320 Family of aircrafts is presented. The costs for offering configuration flexibility to customers are quantified by the expected value of perfect information. The explicit consideration of configuration uncertainty through the use of scenarios is discussed based on the value of the stochastic solution in comparison to the results attained by simplistically using the expected value.