Detecting false testimonies in reputation systems using self-organizing maps

It has been demonstrated that rating trust and reputation of individual nodes is an effective approach in distributed environments in order to improve security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario, the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as bad mouthing attack. In another scenario, a number of entities agree to give positive feedback on an entity (often with adversarial intentions). This attack is known as ballot stuffing. Both attack types can significantly deteriorate the performances of the network. The existing solutions for coping with these attacks are mainly concentrated on prevention techniques. In this work, we propose a solution that detects and isolates the abovementioned attackers, impeding them in this way to further spread their malicious activity. The approach is based on detecting outliers using clustering, in this case self-organizing maps. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrate the capability of the approach in detecting both bad mouthing and ballot stuffing attack in various scenarios.

Explointing FPGA block memories for protected cryptographic implementations

Modern Field Programmable Gate Arrays (FPGAs) are power packed with features to facilitate designers. Availability of features like huge block memory (BRAM), Digital Signal Processing (DSP) cores, embedded CPU makes the design strategy of FPGAs quite different from ASICs. FPGA are also widely used in security-critical application where protection against known attacks is of prime importance. We focus ourselves on physical attacks which target physical implementations. To design countermeasures against such attacks, the strategy for FPGA designers should also be different from that in ASIC. The available features should be exploited to design compact and strong countermeasures. In this paper, we propose methods to exploit the BRAMs in FPGAs for designing compact countermeasures. BRAM can be used to optimize intrinsic countermeasures like masking and dual-rail logic, which otherwise have significant overhead (at least 2X). The optimizations are applied on a real AES-128 co-processor and tested for area overhead and resistance on Xilinx Virtex-5 chips. The presented masking countermeasure has an overhead of only 16% when applied on AES. Moreover Dual-rail Precharge Logic (DPL) countermeasure has been optimized to pack the whole sequential part in the BRAM, hence enhancing the security. Proper robustness evaluations are conducted to analyze the optimization for area and security.

Exploring cognition processes in second language acquisition: the case of cognates and false-friends in EST

This article explores one aspect of the processing perspective in L2 learning in an EST context: the processing of new content words, in English, of the type ‘cognates’ and ‘false friends’, by Spanish speaking engineering students. The paper does not try to offer a comprehensive overview of language acquisition mechanisms, but rather it is intended to review more narrowly how our conceptual systems, governed by intricately linked networks of neural connections in the brain, make language development possible, creating, at the same time, some L2 processing problems. The case of ‘cognates and false friends’ in specialised contexts is brought here to illustrate some of the processing problems that the L2 learner has to confront, and how mappings in the visual, phonological and semantic (conceptual) brain structures function in second language processing of new vocabulary. Resumen Este artículo pretende reflexionar sobre un aspecto de la perspectiva del procesamiento de segundas lenguas (L2) en el contexto del ICT: el procesamiento de palabras nuevas, en inglés, conocidas como “cognados” y “falsos amigos”, por parte de estudiantes de ingeniería españoles. No se pretende ofrecer una visión completa de los mecanismos de adquisición del lenguaje, más bien se intenta mostrar cómo nuestro sistema conceptual, gobernado por una complicada red de conexiones neuronales en el cerebro, hace posible el desarrollo del lenguaje, aunque ello conlleve ciertas dificultades en el procesamiento de segundas lenguas. El caso de los “cognados” y los “falsos amigos”, en los lenguajes de especialidad, se trae para ilustrar algunos de los problemas de procesamiento que el estudiante de una lengua extranjera tiene que afrontar y el funcionamiento de las correspondencias entre las estructuras visuales, fonológicas y semánticas (conceptuales) del cerebro en el procesamiento de nuevo vocabulario.

Star dust memories, or how to detect allergen traces in powder foods

Allergies and food intolerances are at the forefront of institutional interest (European Regulation No 1169/2011) for their impact on consumer health. Allergies to peanuts and other nuts and gluten intolerance, makes production processes involving mixtures of powders a great concern for the industry, given the need to indicate the existence of traces of any of them. The food industry requires non-destructive and non-invasive methods of quantification that meet sensitivity requirements but also specificity levels. Optical methods such as NIR spectrophotometry or hyper-spectral image are currently some of the technologies that show potential success. This is the context of this paper that evaluates how to use NIR spectroscopy (900-1600nm) to detect traces of 15 different kinds of nuts and 20 other flours.