Abstract

This paper presents a model for expressing control system failures and attacks on control protocols that involve the exchange of messages. Control failures and attacks are modeled using the notion of an attacker who can block and/or fabricate messages. These two attack mechanisms can cover a variety of scenarios ranging from control failures in the Waterloo Campaign to cyber attacks on oil pipelines. The model helps provide a comprehensive understanding of control system failures and attacks, which supports the development of strategies for attack as well as defense. Document type: Part of book or chapter of book

Abstract

In this paper, a comparative study between a hybrid technique that combines a Genetic Algorithm with a Cross Entropy method to optimize Fuzzy Rule-Based Systems, and literature techniques is presented. These techniques are applied to traffic congestion datasets in order to determine their performance in this area. Different types of datasets have been chosen. The used time horizons are 5, 15 and 30 min. Results show that the hybrid technique improves those results obtained by the techniques of the state of the art. In this way, the performed experimentation shows the competitiveness of the proposal in this area of application. Document type: Part of book or chapter of book

Abstract

We have developed a formal definition of correctness for pipelines that ensures that transactions terminate and satisfy a functional specification. This definition separates the correctness criteria associated with the pipelining aspects of a design from the functional relationship between input and output transactions. Using this definition, we developed and formally verified a technique that divides the verification of a pipeline into two separate tasks: proving that the pipelining circuitry meets the pipelining correctness criteria and that the datapath and control circuitry meet the functional specification. The first proof is data independent (except for pipelines that use data-dependent control). The second proof is purely combinational: there is no notion of time and each possible input transaction can be dealt with independently. In addition, we have created a framework that structures and simplifies the proof of the pipelining circuitry. Document type: Part of book or chapter of book

Abstract

This paper identifies and discusses a set of criteria relevant to assess the impact of using different media in the design of user interfaces for safety-critical systems. An evaluation of different options concerning the allocation of such media during the design of an application in the Air Traffic Control domain is shown to illustrate and clarify our approach. Particular attention is paid on how different choices in allocating tasks among air traffic controllers affect usability and safety of operators' interactions. Document type: Part of book or chapter of book

Abstract

The measurement of the mental workload during real tasks by means of neurophysiological signals is still challenging. The employment of Machine Learning techniques has allowed a step forward in this direction, however, most of the work has dealt with binary classification. This study proposed to examine the surveys already performed in the context of EEG-based workload classification and to test different machine learning algorithms on real multitasking activity like the Air Traffic Management. The results obtained on 35 professional Air Traffic Controllers showed that a KNN algorithm allows discriminating up to three workload levels (low, medium and high) with more than 84% of accuracy on average. Moreover, in such realistic employment it emerges how important is to opportunely choose the set of features to ward off that task-related confounds could affect the workload assessment. Document type: Part of book or chapter of book

Abstract

In the recent years, more and more modern cars have been equipped with perception capabilities. One of the key applications of such perception systems is the estimation of a risk of collision. This is necessary for both Advanced Driver Assistance Systems and Autonomous Navigation. Most approach for risk estimation propose to detect and track the dynamic objects in the scene. Then the risk is estimated as a Time To Collision (TTC) by projecting the object’s trajectory in the future. In this paper, we propose a new grid-based approach for collision risk prediction, based on the Hybrid-Sampling Bayesian Occupancy Filter framework. The idea is to compute an estimation of the TTC for each cell of the grid, instead of reasoning on objects. This strategy avoids to solve the difficult problem of multi-objects detection and tracking and provides a probabilistic estimation of the risk associated to each TTC value. After promising initial results, we propose in this paper to evaluate the relevance of the method for real on-road applications, by using a real-time implementation of our method in an experimental vehicle. Document type: Part of book or chapter of book

Abstract

Peer-to-peer networking enjoys euphoric support and fierce resistance simultaneously, and for the same reasons. It presents a model where decentralization and lack of structure, hierarchy and control are promoted. Although significant research is carried out to tackle individual issues arising from that paradigm, there has been no obvious approach for evening out differences on a more general basis. In this paper we introduce a framework and provide implementation techniques for such an approach. The framework aims at integrating partial techniques that solve individual problems and has been designed for flexibility. The integrated approach we are proposing includes forming and maintaining of peer-to-peer overlays, controlling the underlying topology being formed, limiting the signaling traffic being generated and optimizing the payload traffic. Document type: Part of book or chapter of book

Abstract

International audience; This paper presents our approach integrating a high level of intelligence within telecommunication networks. Artificial intelligence has proved its efficiency in resolving complex issues in different fields like air traffic control, robotics, and medical diagnosis. However its usage in telecommunication networks is still very moderated. The main objectives of our framework is to encourage the deployment of techniques characterized by a high level of intelligence – inspired from the artificial intelligence domain in networking. For this reason, we build an extension, with intelligent capabilities, to the J-Sim simulation environment. This extension proposes an intelligent package having the essential entities required for simulating intelligent features. Using this intelligent package and the abstract node model (INET) proposed by J-Sim for network simulations, it will be possible to test the efficiency of integrating intelligent techniques in networking. Document type: Part of book or chapter of book

Abstract

Peer-to-peer networks have often been touted as the ultimate solution to scalability. Although cooperative techniques have been initially used almost exclusively for content lookup and sharing, one of the most promising application of the peer-to-peer paradigm is to capitalize the bandwidth of client peers to quickly distribute large content and withstand flash-crowds (i.e., a sudden increase in popularity of some online content). Cooperative content distribution is based on the premise that the capacity of a network is as high as the sum of the resources of its nodes: the more peers in the network, the higher its aggregate bandwidth, and the better it can scale and serve new peers. Such networks can thus spontaneously adapt to the demand by taking advantage of available resources. In this paper, we evaluate the use of peer-to-peer networks for content distribution under various system assumptions, such as peer arrival rates, bandwidth capacities, cooperation strategies, or peer lifetimes. We argue that the self-scaling and self-organizing properties of cooperative networks pave the way for cost-effective, yet highly efficient and robust content distribution. Document type: Part of book or chapter of book