ODIN: Obfuscation-based privacy-preserving consensus algorithm for Decentralized Information fusion in smart device Networks

The large spread of sensors and smart devices in urban infrastructures are motivating research in the area of the Internet of Things (IoT) to develop new services and improve citizens’ quality of life. Sensors and smart devices generate large amounts of measurement data from sensing the environment, which is used to enable services such as control of power consumption or traffic density. To deal with such a large amount of information and provide accurate measurements, service providers can adopt information fusion, which given the decentralized nature of urban deployments can be performed by means of consensus algorithms. These algorithms allow distributed agents to (iteratively) compute linear functions on the exchanged data, and take decisions based on the outcome, without the need for the support of a central entity. However, the use of consensus algorithms raises several security concerns, especially when private or security critical information is involved in the computation. In this article we propose ODIN, a novel algorithm allowing information fusion over encrypted data. ODIN is a privacy-preserving extension of the popular consensus gossip algorithm, which prevents distributed agents from having direct access to the data while they iteratively reach consensus; agents cannot access even the final consensus value but can only retrieve partial information (e.g., a binary decision). ODIN uses efficient additive obfuscation and proxy re-encryption during the update steps and garbled circuits to make final decisions on the obfuscated consensus. We discuss the security of our proposal and show its practicability and efficiency on real-world resource-constrained devices, developing a prototype implementation for Raspberry Pi devices

ODIN: Obfuscation-based privacy-preserving consensus algorithm for Decentralized Information fusion in smart device Networks

The large spread of sensors and smart devices in urban infrastructures are motivating research in the area of the Internet of Things (IoT) to develop new services and improve citizens’ quality of life. Sensors and smart devices generate large amounts of measurement data from sensing the environment, which is used to enable services such as control of power consumption or traffic density. To deal with such a large amount of information and provide accurate measurements, service providers can adopt information fusion, which given the decentralized nature of urban deployments can be performed by means of consensus algorithms. These algorithms allow distributed agents to (iteratively) compute linear functions on the exchanged data, and take decisions based on the outcome, without the need for the support of a central entity. However, the use of consensus algorithms raises several security concerns, especially when private or security critical information is involved in the computation. In this article we propose ODIN, a novel algorithm allowing information fusion over encrypted data. ODIN is a privacy-preserving extension of the popular consensus gossip algorithm, which prevents distributed agents from having direct access to the data while they iteratively reach consensus; agents cannot access even the final consensus value but can only retrieve partial information (e.g., a binary decision). ODIN uses efficient additive obfuscation and proxy re-encryption during the update steps and garbled circuits to make final decisions on the obfuscated consensus. We discuss the security of our proposal and show its practicability and efficiency on real-world resource-constrained devices, developing a prototype implementation for Raspberry Pi devices

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety

3rd EGEE User Forum

We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum

Abordagem de Anotações para o Suporte da Gestão Energética de Software em Modelos AMALTHEA

The automotive industry is continuously introducing innovative software features to provide more efficient, safe, and comfortable solutions. Despite the several benefits to the consumer, the evolution of automotive software is also reflected in several challenges, presenting a growing complexity that hinders its development and integration. The adoption of standards and appropriate development methods becomes essential to meet the requirements of the industry. Furthermore, the expansion of automotive software systems is also driving a considerable growth in the number of electronic components installed in a vehicle, which has a significant impact on the electric energy consumption. Thus, the focus on non-functional energy requirements has become increasingly important. This work presents a study focused on the evolution of automotive software considering the development standards, methodologies, as well as approaches for energy requirements management. We propose an automatic and self-contained approach for the support of energy properties management, adopting the model-based open-source framework AMALTHEA. From the analysis of execution or simulation traces, the energy consumption estimation is provided at a fine-grained level and annotated in AMALTHEA models. Thus, we enable the energy analysis and management of the system throughout the entire lifecycle. Additionally, this solution is in line with the AUTOSAR Adaptive standard, allowing the development of energy management strategies for automatic, dynamic, and adaptive systems.A indústria automotiva encontra-se constantemente a introduzir funcionalidades inovadoras através de software, para oferecer soluções mais eficientes, seguras e confortáveis. Apesar dos diversos benefícios para o consumidor, a evolução do software automóvel também se reflete em diversos desafios, apresentando uma crescente complexidade que dificulta o seu desenvolvimento e integração. Desta forma, a adoção de normas e metodologias adequadas para o seu desenvolvimento torna-se essencial para cumprir os requisitos do setor. Adicionalmente, esta expansão das funcionalidades suportadas por software é fonte de um aumento considerável do número de componentes eletrónicos instalados em automóveis. Consequentemente, existe um impacto significativo no consumo de energia elétrica dos sistemas automóveis, sendo cada vez mais relevante o foco nos requisitos não-funcionais deste domínio. Este trabalho apresenta um estudo focado na evolução do software automotivo tendo em conta os padrões e metodologias de desenvolvimento desta área, bem como abordagens para a gestão de requisitos de energia. Através da adoção da ferramenta AMALTHEA, uma plataforma open-source de desenvolvimento baseado em modelos, é proposta uma abordagem automática e independente para a análise de propriedades energéticas. A partir da análise de traços de execução ou de simulação, é produzida uma estimativa pormenorizada do consumo de energia, sendo esta anotada em modelos AMALTHEA. Desta forma, torna-se possível a análise e gestão energética ao longo de todo o ciclo de vida do sistema. Salienta-se que a solução se encontra alinhada com a norma AUTOSAR Adaptive, permitindo o desenvolvimento de estratégias para a gestão energética de sistemas automáticos, dinâmicos e adaptativos

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.