An Unsupervised Approach for Automotive Driver Identification

The adoption of on-vehicle monitoring devices allows different entities to gather valuable data about driving styles, which can be further used to infer a variety of information for different purposes, such as fraud detection and driver profiling. In this paper, we focus on the identification of the number of people usually driving the same vehicle, proposing a data analytic work-flow specifically designed to address this problem. Our approach is based on unsupervised learning algorithms working on non-invasive data gathered from a specialized embedded device. In addition, we present a preliminary evaluation of our approach, showing promising driver identification capabilities and a limited computational effort

A Novel Regular Format for X.509 Digital Certificates

Digital certificates are one of the key components to ensure secure network communications. The complexity of the certificate standard, ITU-R-X.509, has led to a number of breaches in the TLS protocol security due to certificate misinterpretation by TLS libraries. We argue that the root cause of such an issue is the complexity of the certificate structure, which can be gauged with the framework of formal language theory: the language describing digital certificates is context sensitive. Such a complexity led to handcrafted X.509 parsers, resulting in implementations which are not guaranteed to perform correct language recognition. We highlight the issues in X.509, and propose a new format for digital certificates, designed to be parsed effectively and efficiently, while retaining the same semantic expressiveness. The certificate format can be deployed gradually, is fully specified as a regular language, and is specified as a formal grammar from which a provably correct parser can be automatically derived. We validate the effectiveness of our proposal, and the linear running time provided by the approach, generating an instance of the parser with a production grade lexer/parser generation framework

Modeling and Simulation of Electromutagenic Processes for Multiscale Modification of Concrete

Concrete contains numerous pores that allow degradation when chloride ions migrate through these paths and make contact with the steel reinforcement in a structure. Chlorides come mainly from the sea or de-icing salts. To keep the reinforcement from being exposed to chlorides, it is possible to electrokinetically force nanoparticles into the pores, blocking access. This procedure is called electrokinetic nanoparticle treatment. When the particles used are reactive in nature, the process becomes both structural and chemical in nature. We use the term electromutagenic processing to describe such extensive electrochemical remodeling. Filling the pores in a block of concrete with solid materials or nanoparticles tends to improve the strength significantly. In this paper, results obtained from modeling and simulation were aimed at multi-scale porosity reduction of concrete. Since nanoparticles and pores were modeled with spheres and cylinders having different sizes, the results were compared with traditional sphere packing problems in mathematics. There were significant differences observed related to the sizes of spheres and allowable boundary conditions. From traditional sphere packing analysis the highest porosity reduction anticipated was 74%. In contrast, the highest pore reduction obtained in this work was approximately 50%, which matched results from actual electrokinetic nanoparticle treatments. This work also compared the analytical and simulation methods used for several sizes of nanoparticles and pores

Accelerating Automotive Analytics: The M2DC Appliance Approach

The Modular Microserver DataCenter (M2DC) project provides lowenergy, configurable, heterogeneous servers for applications that focus on the elaboration of large data sets, but can take advantage of performance enhancement provided by transparent acceleration techniques. In this paper, we exemplify the M2DC approach through one of the project’s use cases, namely automotive Internet of Things analytics. We present the main goals of the use case and we show how an appropriate M2DC microserver can be used to accelerate the application without significant modifications to its code

Efficient Oblivious Substring Search via Architectural Support

Performing private and efficient searches over encrypted outsourced data enables a flourishing growth of cloud based services managing sensitive data as the genomic, medical and financial ones. We tackle the problem of building an efficient indexing data structure, enabling the secure and private execution of substring search queries over an outsourced document collection. Our solution combines the efficiency of an index-based substring search algorithm with the secure-execution features provided by the SGX technology and the access pattern indistinguishability guarantees provided by an Oblivious RAM. To prevent the information leakage from the eventual access pattern side-channel vulnerabilities, we redesign three ORAM algorithms, and perform a comparative evaluation to find the best engineering trade-offs for a privacy-preserving index-based substring search protocol. The practicality of our solution is supported by a response time of about 1 second to retrieve all the positions of a protein in the 3 GB string of the human genome

The M2DC Approach towards Resource-efficient Computing

The H2020 project Modular Microserver DataCentre (M2DC) investigates, develops and demonstrates a modular, highly-efficient, cost-optimized server architecture composed of heterogeneous microserver computing resources. The M2DC architecture can be tailored to meet requirements from various application domains such as image processing, cloud computing or HPC. To achieve this, M2DC is built on three pillars. (1) The RECSjBox, a flexible server architecture fully configurable with respect to application requirements supports the full range of microserver technologies, including low power ARM processors or FPGA accelerators as well as high performance x86 or GPU devices. (2) Advanced management strategies as well as system efficiency enhancements (SEE) improve the behaviour of the system during runtime, thereby addressing application acceleration, communications and monitoring & management. Moreover, an intelligent management module complements the middleware by proactive workload, therma l and power management to increase the energy efficiency. (3) Welldefined interfaces to the software ecosystem enable easy integration of the customized RECSjBox system into the existing data centre landscape. By integrating into OpenStack for bare metal orchestration of the microservers, the applicability in today’s data centre is granted. Current project results include new microserver designs based on ARM64 and Intel Stratix 10. The document presents TCO estimations and baseline benchmarks to show the high potential of accelerators for the targeted applications including image processing, Internet-of-things (IoT) data processing and others

Transition in the waiting-time distribution of price-change events in a global socioeconomic system

The goal of developing a firmer theoretical understanding of inhomogeneous temporal processes–in particular, the waiting times in some collective dynamical system–is attracting significant interest among physicists. Quantifying the deviations between the waiting-time distribution and the distribution generated by a random process may help unravel the feedback mechanisms that drive the underlying dynamics. We analyze the waiting-time distributions of high-frequency foreign exchange data for the best executable bid–ask prices across all major currencies. We find that the lognormal distribution yields a good overall fit for the waiting-time distribution between currency rate changes if both short and long waiting times are included. If we restrict our study to long waiting times, each currency pair’s distribution is consistent with a power-law tail with exponent near to 3.5. However, for short waiting times, the overall distribution resembles one generated by an archetypal complex systems model in which boundedly rational agents compete for limited resources. Our findings suggest that a gradual transition arises in trading behavior between a fast regime in which traders act in a boundedly rational way and a slower one in which traders’ decisions are driven by generic feedback mechanisms across multiple timescales and hence produce similar power-law tails irrespective of currency type. •We quantify the distribution of waiting times between currency price changes.•A gradual transition is observed between short and long waiting times.•Longer waiting times show a power-law tail with exponent near 3.5.•Shorter waiting times can be explained using a model of boundedly rational agents

The M2DC Approach towards Resource-efficient Computing

Agosta G, Barenghi A, Ciesielczyk T, et al. The M2DC Approach towards Resource-efficient Computing. In: Bagnato A, Couceiro R, Monteiro J, Petrovska-Delacrétaz D, Lopes A, Gouveia É, eds. OPPORTUNITIES AND CHALLENGES for European Projects. Volume 1: EPS Portugal 2017/2018. Setúbal, Portugal: SCITEPRESS; 2017: 150-176