References of "Engel, Thomas 50001752"
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See detailRevisiting Gaussian Mixture Models for Driver Identification
Jafarnejad, Sasan UL; Castignani, German UL; Engel, Thomas UL

in IEEE International Conference on Vehicular Electronics and Safety (ICVES) (ICVES 2018) (in press)

The increasing penetration of connected vehicles nowadays has enabled driving data collection at a very large scale. Many telematics applications have been also enabled from the analysis of those datasets ... [more ▼]

The increasing penetration of connected vehicles nowadays has enabled driving data collection at a very large scale. Many telematics applications have been also enabled from the analysis of those datasets and the usage of Machine Learning techniques, including driving behavior analysis predictive maintenance of vehicles, modeling of vehicle health and vehicle component usage, among others. In particular, being able to identify the individual behind the steering wheel has many application fields. In the insurance or car-rental market, the fact that more than one driver make use of the vehicle generally triggers extra fees for the contract holder. Moreover being able to identify different drivers enables the automation of comfort settings or personalization of advanced driver assistance (ADAS) technologies. In this paper, we propose a driver identification algorithm based on Gaussian Mixture Models (GMM). We show that only using features extracted from the gas pedal position and steering wheel angle signals we are able to achieve near 100 accuracy in scenarios with up to 67 drivers. In comparison to the state-of-the-art, our proposed methodology has lower complexity, superior accuracy and offers scalability to a larger number of drivers. [less ▲]

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See detailPOSTER: WLAN Device Fingerprinting using Channel State Information (CSI)
Adamsky, Florian UL; Retunskaia, Tatiana UL; Schiffner, Stefan UL et al

in 11th ACM Conference on Security and Privacy in Wireless and Mobile Networks (ACM WiSec) (2018, June)

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See detailPerformance Analysis of CoAP under Satellite Link Disruption
Giotti, Domenico UL; Lamorte, Luca UL; Soua, Ridha UL et al

in Performance Analysis of CoAP under Satellite Link Disruption (2018, June)

Internet of Things (IoT) devices connectivity is steadily increasing in both heterogeneity and sophistication. However, classical and emerging technology (Wi-Fi, Zigbee, LoRa, etc.) are not able to ... [more ▼]

Internet of Things (IoT) devices connectivity is steadily increasing in both heterogeneity and sophistication. However, classical and emerging technology (Wi-Fi, Zigbee, LoRa, etc.) are not able to support well IoT applications, when terrestrial networks are no longer available (e.g., in remote not habitable areas, in the occurrence of calamities). Subsequently, the only way forward is to transmit IoT data over satellite. The integrated satellite-terrestrial networks are emerging as a promising solution to ensure ubiquitous IoT connectivity, higher throughput and reliability. Being different by design, IoT protocols’ tuning is needed to integrate terrestrial and satellite segments. In the current paper, we evaluate the performances of CoAP, the well-known lightweight application protocol for IoT in an integrated scenario, taking into account the satellite link disruption. The key findings of our study, conducted using the OpenSAND simulator, show that decreasing the value of congestion control parameters proposed by the standard [1], mainly ACK_TIMEOUT and ACK_RANDOM_FACTOR, is crucial to achieve lower end-to-end delays and higher packet delivery ratio. [less ▲]

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See detailROADNET: Fairness- and Throughput-Enhanced Scheduling for Content Dissemination in VANETs
Di Maio, Antonio UL; Soua, Ridha UL; Palattella, Maria Rita UL et al

in ROADNET: Fairness- and Throughput-Enhanced Scheduling for Content Dissemination in VANETs (2018, May 23)

The increasing demand for bandwidth by applications in Vehicular Ad-Hoc Networks (VANETs), combined with the increasing number of their users, stresses the importance of data dissemination schemes that ... [more ▼]

The increasing demand for bandwidth by applications in Vehicular Ad-Hoc Networks (VANETs), combined with the increasing number of their users, stresses the importance of data dissemination schemes that strike a balance between network throughput and user fairness. Ensuring this balance is challenging in vehicular networks, which are characterized by a high dynamism of the network topology, volatility of intervehicular links, and heterogeneity of the exchanged content. For these reasons, we hereby introduce ROADNET, a cooperative content dissemination scheme for VANETs. Leveraging on the Software Defined Networking (SDN) paradigm, ROADNET provides a trade-off between network throughput and user fairness by exploiting the logical centralized control of SDN and the multichannel operation of the IEEE 1609.4 standard. Realistic simulation results show that our scheme outperforms prior works in terms of both throughput (≈ 36%) and fairness (≈ 6%), providing high channel load balance (σ ≈ 1%). [less ▲]

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See detailNon-intrusive Distracted Driving Detection Based on Driving Sensing Data
Jafarnejad, Sasan UL; Castignani, German UL; Engel, Thomas UL

in 4th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2018) (2018, March)

Nowadays Internet-enabled phones have become ubiquitous, and we all witness the flood of information that often arrives with a notification. Most of us immediately divert our attention to our phones even ... [more ▼]

Nowadays Internet-enabled phones have become ubiquitous, and we all witness the flood of information that often arrives with a notification. Most of us immediately divert our attention to our phones even when we are behind the wheel. Statistics show that drivers use their phone on 88% of their trips and on 2015 in the UnitedKingdom 25% of the fatal accidents were caused by distraction or impairment. Therefore there is need to tackle this issue. However, most of the distraction detection methods either use expensive dedicated hardware and/or they make use of intrusive or uncomfortable sensors. We propose distracted driving detection mechanism using non-intrusive vehicle sensor data. In the proposed method 9 driving signals are used. The data is collected, then two sets of statistical and cepstral features are extracted using a sliding window process, further a classifier makes a prediction for each window frame, lastly, a decision function takes the last l predictions and makes the final prediction. We evaluate the subject independent performance of the proposed mechanism using a driving dataset consisting of 13 drivers. We show that performance increases as the decision window become larger.We achieve the best results using a Gradient Boosting classifier with a decision window of total duration 285seconds which yield ROC AUC of 98.7%. [less ▲]

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See detailMachine Learning for Reliable Network Attack Detection in SCADA Systems
Lopez Perez, Rocio; Adamsky, Florian UL; Soua, Ridha UL et al

in 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications (IEEE TrustCom-18) (2018)

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See detailThe State of Affairs in BGP Security: A Survey of Attacks and Defenses
Mitseva, Asya UL; Panchenko, Andriy UL; Engel, Thomas UL

in Computer Communications (2018)

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See detailMulti-Access Edge Computing for Vehicular Networks: a Position Paper
Soua, Ridha UL; Turcanu, Ion UL; Adamsky, Florian UL et al

in 2018 IEEE Global Communications Conference: Workshops: Vehicular Networking and Intelligent Transportation Systems (2018)

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See detailDemo: MAMBA: A Platform for Personalised Multimodal Trip Planning
Faye, Sébastien UL; Cantelmo, Guido UL; Tahirou, Ibrahim UL et al

Software (2017)

In recent years, multimodal transportation has become a challenging approach to route planning. Most existing planning systems usually rely on data sourced from different organisations, enabling the user ... [more ▼]

In recent years, multimodal transportation has become a challenging approach to route planning. Most existing planning systems usually rely on data sourced from different organisations, enabling the user to select a limited number of routing strategies. As part of the MAMBA project, developed in Luxembourg until 2017, we have been interested in the potential benefits of multimodal mobility systems. A key factor has been integrated into our studies: the need for a personalised experience at user level, whether when selecting the means of transport or describing user habits (e.g. route style, environment). In this context, we have developed a platform for planning personalised multimodal trips, broken down into the three main modules presented in this demonstration. More importantly, this platform has been developed to facilitate the daily mobility of people in Luxembourg, and considers datasets and characteristics that are specific to this region, which has an exceptionally high volume of daily commuting between Luxembourg and neighbouring countries. [less ▲]

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See detailPoster: Characterizing Driving Behaviors Through a Car Simulation Platform
Faye, Sébastien UL; Jafarnejad, Sasan UL; Costamagna, Juan UL et al

Poster (2017, November 27)

Human mobility has opened up to many themes in recent years. Human behavior and how a driver might react to certain situations, whether dangerous (e.g. an accident) or simply part of the evolution of new ... [more ▼]

Human mobility has opened up to many themes in recent years. Human behavior and how a driver might react to certain situations, whether dangerous (e.g. an accident) or simply part of the evolution of new technologies (e.g. autonomous driving), leaves many avenues to be explored. Although experiments have been deployed in real situations, it remains difficult to encounter the conditions that certain studies may require. For this reason, we have set up a driving simulator (comprising several modules) that is able to reproduce a realistic driving environment. Although, as the literature has already demonstrated, the conditions are often far from reality, simulation platforms are nonetheless capable of reproducing an incredibly large number of scenarios on the fly. In this poster, we explain how we conceived the simulator, as well as the system we developed for collecting metrics on both the driver and the simulation environment. In addition, we take advantage of this conference to publicly share a dataset consisting of 25 drivers performing the same road circuit on the "Project Cars" game. [less ▲]

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See detailAnalysis of Fingerprinting Techniques for Tor Hidden Services
Panchenko, Andriy UL; Mitseva, Asya UL; Henze, Martin et al

in Proceedings of the 24th ACM Computer and Communications Security (ACM CCS) 16th Workshop on Privacy in the Electronic Society (ACM WPES 2017) (2017, October 31)

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See detailCharacterizing Driving Environments Through Bluetooth Discovery
Bronzi, Walter UL; Faye, Sébastien UL; Frank, Raphaël UL et al

Scientific Conference (2017, October)

Within the world of wireless technologies, Bluetooth has recently been at the forefront of innovation. It is becoming increasingly relevant for vehicles to become aware of their surroundings. Therefore ... [more ▼]

Within the world of wireless technologies, Bluetooth has recently been at the forefront of innovation. It is becoming increasingly relevant for vehicles to become aware of their surroundings. Therefore, having knowledge of nearby Bluetooth devices, both inside and outside other vehicles, can provide the listening vehicles with enough data to learn about their environment. In this paper, we collect and analyze a dataset of Bluetooth Classic (BC) and Low Energy (BLE) discoveries. We evaluate their respective characteristics and ability to provide context-aware information from a vehicular perspective. By taking a look at data about the encountered devices, such as GPS location, quantity, quality of signal and device class information, we infer distinctive behaviors between BC and BLE relative to context and application. For this purpose, we propose a set a features to train a classifier for the recognition of different driving environments (i.e. road classes) from Bluetooth discovery data alone. Comparing the performance of our classifier with different sampling parameters, the presented results indicate that, with our feature selection, we are able to predict with reasonable confidence up to three classes (Highway, City, Extra-Urban) by using only discovery data and no geographical information. This outcome gives promising results targeted at low energy and privacy-friendly applications and can open up a wide range of research directions. [less ▲]

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See detailEstimating Urban Road Traffic States Using Mobile Network Signaling Data
Derrmann, Thierry UL; Frank, Raphaël UL; Viti, Francesco UL et al

in Abstract book of the 20th International Conference on Intelligent Transportation Systems (2017, October)

It is intuitive that there is a causal relationship between human mobility and signaling events in mobile phone networks. Among these events, not only the initiation of calls and data sessions can be used ... [more ▼]

It is intuitive that there is a causal relationship between human mobility and signaling events in mobile phone networks. Among these events, not only the initiation of calls and data sessions can be used in analyses, but also handovers between different locations that reflect mobility. In this work, we investigate if handovers can be used as a proxy metric for flows in the underlying road network, especially in urban environments. More precisely, we show that characteristic profiles of handovers within and between clusters of mobile network cells exist. We base these profiles on models from road traffic flow theory, and show that they can be used for traffic state estimation using floating-car data as ground truth. The presented model can be beneficial in areas with good mobile network coverage but low road traffic counting infrastructure, e.g. in developing countries, but also serve as an additional predictor for existing traffic state monitoring systems. [less ▲]

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See detailA centralized approach for setting floating content parameters in VANETs
Di Maio, Antonio UL; Soua, Ridha UL; Palattella, Maria Rita et al

in A centralized approach for setting floating content parameters in VANETs (2017, July 20)

Floating Content (FC) has recently been proposed as an attractive application for mobile networks, such as VANETs, to operate opportunistic and distributed content sharing over a given geographic area ... [more ▼]

Floating Content (FC) has recently been proposed as an attractive application for mobile networks, such as VANETs, to operate opportunistic and distributed content sharing over a given geographic area, namely Anchor Zone (AZ). FC performances are tightly dependent on the AZ size, which in literature is classically chosen by the node that generates the floating message. In the present work, we propose a method to improve FC performances by optimizing the AZ size with the support of a Software Defined Network (SDN) controller, which collects mobility information, such as speed and position, of the vehicles in its coverage range. [less ▲]

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See detailHow Mobile Phone Handovers reflect Urban Mobility: A Simulation Study
Derrmann, Thierry UL; Frank, Raphaël UL; Engel, Thomas UL et al

in Proceedings of the 5th IEEE Conference on Models and Technologies for Intelligent Transportation Systems. (2017, June 26)

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See detailAn Efficient Service Channel Allocation Scheme in SDN-enabled VANETs
Radhakrishnan, Ila; Soua, Ridha UL; Palattella, Maria Rita UL et al

in An Efficient Service Channel Allocation Scheme in SDN-enabled VANETs (2017, June)

Providing infotainment services in Vehicular Adhoc Networks (VANETs) is a key functionality for the future intelligent transportation systems. However, the unique features of vehicular networks such as ... [more ▼]

Providing infotainment services in Vehicular Adhoc Networks (VANETs) is a key functionality for the future intelligent transportation systems. However, the unique features of vehicular networks such as high velocity, intermittent communication links and dynamic density can induce severe performances degradation for infotainment services running on the six Service Channels (SCHs) available in the Dedicated Short Range Communication (DSRC). Although, the Wireless Access in the Vehicular Environment (WAVE) has been proposed for VANETs to support these applications and guarantee the QoS by proposing four different access categories, no service channel scheme has been proposed to ensure fair and interference-aware allocation. To fill this gap, in this work we propose ESCiVA, an Efficient Service Channel allocation Scheme in SDN-enabled VAnets to balance service traffic on the six SCHs and mitigate interferences between services provided on adjacent channels. Extensive simulation results confirm that ESCiVA outperforms the basic SCH allocation method, defined in the WAVE standard [less ▲]

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See detailA Multi-Pronged Approach to Adaptive and Context Aware Content Dissemination in VANETs
Duarte, Joao; Kalogeiton, Eirini; Soua, Ridha UL et al

in Mobile Networks and Applications (2017)

Content dissemination in Vehicular Ad-hoc Networks (VANETs) has the potential to enable a myriad of applications, ranging from advertising, traffic and emergency warnings to infotainment. This variety in ... [more ▼]

Content dissemination in Vehicular Ad-hoc Networks (VANETs) has the potential to enable a myriad of applications, ranging from advertising, traffic and emergency warnings to infotainment. This variety in applications and services calls for mechanisms able to optimize content storing, retrieval and forwarding among vehicles, without jeopardizing network resources. Content Centric Networking (CCN), takes advantage of inherent content redundancy in the network in order to decrease the utilization of network resources, improve response time and content availability, coping efficiently with some of the effects of mobility. Floating Content (FC), on the other hand, holds potential to implement efficiently a large amount of vehicular applications thanks to its property of geographic content replication, while Software Defined Networking (SDN), is an attractive solution for the lack of flexibility and dynamic programmability that characterizes current VANET architectures. By implementing a logical centralization of the network, SDN enables dynamic and efficient management of network resources. In this paper, for a few reference scenarios, we illustrate how approaches that combine CCN, FC and SDN enable an innovative adaptive VANET architecture able to efficiently accommodate to intermittent connectivity, fluctuating node density and mobility patterns on one side and application performance and network resources on the other side, aiming to achieve high QoS. For each scenario, we highlight the main open research challenges, and we describe possible solutions to improve content dissemination and reduce replication without affecting content availability. [less ▲]

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See detailAn Open Dataset for Human Activity Analysis using Smart Devices
Faye, Sébastien UL; Louveton, Nicolas UL; Jafarnejad, Sasan UL et al

Report (2017)

The study of human mobility and activities has opened up to an incredible number of studies in the past, most of which included the use of sensors distributed on the body of the subject. More recently ... [more ▼]

The study of human mobility and activities has opened up to an incredible number of studies in the past, most of which included the use of sensors distributed on the body of the subject. More recently, the use of smart devices has been particularly relevant because they are already everywhere and they come with accurate miniaturized sensors. Whether it is smartphones, smartwatches or smartglasses, each device can be used to describe complementary information such as emotions, precise movements, or environmental conditions. In this short paper, we release the applications we have developed and an example of a collected dataset. We propose that opening multi-sensors data from daily activities may enable new approaches to studying human behavior. [less ▲]

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See detailTowards a Real-Time Driver Identification Mechanism Based on Driving Sensing Data
Jafarnejad, Sasan UL; Castignani, German UL; Engel, Thomas UL

in 20th International Conference on Intelligent Transportation Systems (ITSC) (2017)

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See detailCoordination Mechanisms for Floating Content in Realistic Vehicular Scenario
Manzo, Gaetano; Soua, Ridha UL; Di Maio, Antonio UL et al

in Coordination Mechanisms for Floating Content in Realistic Vehicular Scenario (2017)

The increasing interest in vehicular communications draws attention to scalability and network congestion problems and therefore on techniques to offload the traffic, typically carried through the ... [more ▼]

The increasing interest in vehicular communications draws attention to scalability and network congestion problems and therefore on techniques to offload the traffic, typically carried through the infrastructure, to the Vehicle-to-vehicle (V2V) network. Floating content (FC) represents a promising paradigm to share ephemeral content without direct support from infrastructure. It is based on constraining geographically within the Anchor Zone (AZ) the opportunistic replication of a given content among vehicles, in a way that strikes a balance between minimization of resource usage and content availability. Existing works on FC performance modeling are based on standard, homogeneous synthetic mobility models, and it is hence unclear how they actually fit in realistic mobility scenarios. Moreover, the approaches to FC dimensioning they propose assume users have full knowledge of Spatio-temporal mobility patterns, which is hard to achieve in practice. Finally, despite FC is an infrastructure-less communication paradigm, some form of infrastructure support could be available in the vast majority of those application scenarios for which it has been proposed. In this paper, we perform a first attempt at tackling these issues. We focus on how to dimension an Anchor Zone in a realistic vehicular scenario. We propose the first set of simple dimensioning strategies, based on the estimation of some key mobility parameters and of FC performance. We assess such strategies on measurement-based vehicular traces, providing a first indication of their relative performance, and of the feasibility of FC in practical scenarios. [less ▲]

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