Trojans in Early Design Steps—An Emerging Threat

Hardware Trojans inserted by malicious foundries during integrated circuit manufacturing have received substantial attention in recent years. In this paper, we focus on a different type of hardware Trojan threats: attacks in the early steps of design process. We show that third-party intellectual property cores and CAD tools constitute realistic attack surfaces and that even system specification can be targeted by adversaries. We discuss the devastating damage potential of such attacks, the applicable countermeasures against them and their deficiencies

Topology optimization of multiple anisotropic materials, with application to self-assembling diblock copolymers

We propose a solution strategy for a multimaterial minimum compliance topology optimization problem, which consists in finding the optimal allocation of a finite number of candidate (possibly anisotropic) materials inside a reference domain, with the aim of maximizing the stiffness of the body. As a relevant and novel application we consider the optimization of self-assembled structures obtained by means of diblock copolymers. Such polymers are a class of self-assembling materials which spontaneously synthesize periodic microstructures at the nanoscale, whose anisotropic features can be exploited to build structures with optimal elastic response, resembling biological tissues exhibiting microstructures, such as bones and wood. For this purpose we present a new generalization of the classical Optimality Criteria algorithm to encompass a wider class of problems, where multiple candidate materials are considered, the orientation of the anisotropic materials is optimized, and the elastic properties of the materials are assumed to depend on a scalar parameter, which is optimized simultaneously to the material allocation and orientation. Well-posedness of the optimization problem and well-definition of the presented algorithm are narrowly treated and proved. The capabilities of the proposed method are assessed through several numerical tests

Du loup. Force et loi

For elucidating the relation between violence and justice, that gives rise to the phrase «force of law», the figure of wolf, the lupus in fabula, occupies a strategic place in the western philosophical and political discourse. The double reading –or writing– of such a phrase in a text by Solon, because of a lapsus calami – indeed a masterly slip of the pen, as Derrida reminds us– allows us to see the –paradoxical– double face of the sovereign kratos: that of force without law and outside the law that establishes the law, and that of force incorporated into the law to accomplish justice. The figure of the wolf embodies this paradox of sovereignty.Para esclarecer la relación entre violencia y justicia que cristaliza en el sintagma «fuerza de ley», la figura del lobo, el lupus in fabula, ocupa un lugar estratégico en el discurso filosófico-político de occidente. La doble lectura –o escritura– de dicho sintagma en un texto de Solón debida a un lapsus calami –lapsus magistral sin duda, como recuerda Derrida– nos permite ver la doble cara –paradójica– del kratos soberano: la de la fuerza sin ley y fuera de la ley que establece la ley, y la de la fuerza incorporada a la ley para la realización de la justicia. En la figura del lobo se encarna esa paradoja de la soberanía.Para esclarecer la relación entre violencia y justicia que cristaliza en el sintagma «fuerza de ley», la figura del lobo, el lupus in fabula, ocupa un lugar estratégico en el discurso filosófico-político de occidente. La doble lectura –o escritura– de dicho sintagma en un texto de Solón debida a un lapsus calami –lapsus magistral sin duda, como recuerda Derrida– nos permite ver la doble cara –paradójica– del kratos soberano: la de la fuerza sin ley y fuera de la ley que establece la ley, y la de la fuerza incorporada a la ley para la realización de la justicia. En la figura del lobo se encarna esa paradoja de la soberanía

Unsupervised Understanding of Location and Illumination Changes in Egocentric Videos

Wearable cameras stand out as one of the most promising devices for the upcoming years, and as a consequence, the demand of computer algorithms to automatically understand the videos recorded with them is increasing quickly. An automatic understanding of these videos is not an easy task, and its mobile nature implies important challenges to be faced, such as the changing light conditions and the unrestricted locations recorded. This paper proposes an unsupervised strategy based on global features and manifold learning to endow wearable cameras with contextual information regarding the light conditions and the location captured. Results show that non-linear manifold methods can capture contextual patterns from global features without compromising large computational resources. The proposed strategy is used, as an application case, as a switching mechanism to improve the hand-detection problem in egocentric videos.Comment: Submitted for publicatio

Optimizar el diagnóstico : la ecuación matemática del examen físico

Fil: Regazzoni, Carlos Javier. Universidad de Buenos Aires. Hospital de Clínicas José de San Martín; Argentina.Fil: Azzato, Francisco. Universidad de Buenos Aires. Hospital de Clínicas José de San Martín; Argentina.Con el examen físico, el médico obtiene una serie de signos que son, o bien manifestación directa, o\nbien signos que permiten inferir la presencia de una enfermedad. Estima una probabilidad, y esto con\nun margen de error debido a la variabilidad. Pero como el rigor de las conclusiones depende del rigor\nde las premisas y del análisis efectuado, es así que la ciencia médica ha puesto proa contra el examen\nfísico en un intento de optimizar su enorme potencial diagnóstico, dando un valor numérico a su\ncerteza (y a su error!)

Left/Right Hand Segmentation in Egocentric Videos

Wearable cameras allow people to record their daily activities from a user-centered (First Person Vision) perspective. Due to their favorable location, wearable cameras frequently capture the hands of the user, and may thus represent a promising user-machine interaction tool for different applications. Existent First Person Vision methods handle hand segmentation as a background-foreground problem, ignoring two important facts: i) hands are not a single "skin-like" moving element, but a pair of interacting cooperative entities, ii) close hand interactions may lead to hand-to-hand occlusions and, as a consequence, create a single hand-like segment. These facts complicate a proper understanding of hand movements and interactions. Our approach extends traditional background-foreground strategies, by including a hand-identification step (left-right) based on a Maxwell distribution of angle and position. Hand-to-hand occlusions are addressed by exploiting temporal superpixels. The experimental results show that, in addition to a reliable left/right hand-segmentation, our approach considerably improves the traditional background-foreground hand-segmentation

Exploring Energy Efficiency of Lightweight Block Ciphers

Abstract. In the last few years, the field of lightweight cryptography has seen an influx in the number of block ciphers and hash functions being proposed. One of the metrics that define a good lightweight design is the energy consumed per unit operation of the algorithm. For block ciphers, this operation is the encryption of one plaintext. By studying the energy consumption model of a CMOS gate, we arrive at the conclusion that the total energy consumed during the encryption operation of an r-round unrolled architecture of any block cipher is a quadratic function in r. We then apply our model to 9 well known lightweight block ciphers, and thereby try to predict the optimal value of r at which an r-round unrolled architecture for a cipher is likely to be most energy efficient. We also try to relate our results to some physical design parameters like the signal delay across a round and algorithmic parameters like the number of rounds taken to achieve full diffusion of a difference in the plaintext/key