References of "Engel, Thomas 50001752"
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See detailAnalysis of Multi-path Onion Routing-based Anonymization Networks
de La Cadena Ramos, Augusto Wladimir UL; Kaiser, Daniel UL; Mitseva, Asya UL et al

in Data and Applications Security and Privacy XXXIII, 2019 (2019, July 15)

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See detailIoT Device Fingerprinting: Machine Learning based Encrypted Traffic Analysis
Msadek, Mohamed Nizar UL; Soua, Ridha UL; Engel, Thomas UL

in The IEEE Wireless Communications and Networking Conference (WCNC) (2019, April 19)

Even in the face of strong encryption, the spectacular Internet of Things (IoT) penetration across sectors such as e-health, energy, transportation, and entertainment is expanding the attack surface ... [more ▼]

Even in the face of strong encryption, the spectacular Internet of Things (IoT) penetration across sectors such as e-health, energy, transportation, and entertainment is expanding the attack surface, which can seriously harm users’ privacy. We demonstrate in this paper that an attacker is able to disclose sensitive information about the IoT device, such as its type,by identifying specific patterns in IoT traffic. To perform the fingerprint attack, we train machine-learning algorithms based on selected features extracted from the encrypted IoT traffic.Extensive simulations involving the baseline approach show that we achieve not only a significant mean accuracy improvement of 18.5% and but also a speedup of 18.39 times for finding the best estimators. Obtained results should spur the attention of policymakers and IoT vendors to secure the IoT devices they bring to market. [less ▲]

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See detailFog Computing as the Key for Seamless Connectivity Handover in Future Vehicular Networks
Palattella, Maria Rita UL; Soua, Ridha UL; Abdelmajid, Khelil et al

in The 34th ACM Symposium On Applied Computing (SAC (2019, April)

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See detailHow Road and Mobile Networks Correlate: Estimating Urban Traffic Using Handovers
Derrmann, Thierry; Frank, Raphaël UL; Viti, Francesco UL et al

in IEEE Transactions on Intelligent Transportation Systems (2019)

We propose a novel way of linking mobile network signaling data to the state of the underlying urban road network. We show how a predictive model of traffic flows can be created from mobile network ... [more ▼]

We propose a novel way of linking mobile network signaling data to the state of the underlying urban road network. We show how a predictive model of traffic flows can be created from mobile network signaling data. To achieve this, we estimate the vehicular density inside specific areas using a polynomial function of the inner and exiting mobile phone handovers performed by the base stations covering those areas. We can then use the aggregated handovers as flow proxies alongside the density proxy to directly estimate an average velocity within an area. We evaluate the model in a simulation study of Luxembourg city and generalize our findings using a real-world data set extracted from the LTE network of a Luxembourg operator. By predicting the real traffic states as measured through floating car data, we achieve a mean absolute percentage error of 11.12%. Furthermore, in our study case, the approximations of the network macroscopic fundamental diagrams (MFD) of road network partitions can be generated. The analyzed data exhibit low variance with respect to a quadratic concave flow-density function, which is inline with the previous theoretical results on MFDs and are similar when estimated from simulation and real data. These results indicate that mobile signaling data can potentially be used to approximate MFDs of the underlying road network and contribute to better estimate road traffic states in urban congested networks. [less ▲]

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See detailAdvancing the Security of Trustworthy Self-IoT (Position Paper)
Msadek, Mohamed Nizar UL; Soua, Ridha UL; Ladid, Latif UL et al

in International Conference on Smart Applications, Communications and Networking (SmartNets) (2018, November)

The Internet of Things (IoT) encompasses many aspects of our daily life, from connected homes and cities through connected vehicles and roads to devices that collaborate independently to achieve a ... [more ▼]

The Internet of Things (IoT) encompasses many aspects of our daily life, from connected homes and cities through connected vehicles and roads to devices that collaborate independently to achieve a specific purpose. Being an example of a largescale self-organizing systems, the IoT should present imperative properties such as autonomy and trustworthiness. However, compared to classical self-organizing systems, IoT has intrinsic characteristics (wide deployment, resource constraints, uncertain environment, etc.) that open up several security challenges. These challenges cannot be solved by existing Autonomic and Organic Computing techniques and therefore new techniques adapted to self-organizing IoT, (that we call Self-IoT) peculiarities are needed. To this end, this paper studies related work in the area of self-organizing IoT, identifies and describes the key research challenges for trustworthy secure Self-IoT and proposes new and tailored existing solutions. [less ▲]

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See detailIoT Application Protocols Optimisation for Future Integrated M2M-Satellite Networks
Soua, Ridha UL; Palattella, Maria Rita UL; Engel, Thomas UL

in IoT Application Protocols Optimisation for Future Integrated M2M-Satellite Networks (2018, October)

Satellites are playing a key role in driving the vision for a truly connected world, providing ubiquitous coverage and reliability in places where no other terrestrial technology could. While the ... [more ▼]

Satellites are playing a key role in driving the vision for a truly connected world, providing ubiquitous coverage and reliability in places where no other terrestrial technology could. While the potentials of satellites for IoT are well recognised, to allow a smooth integration of M2M and satellite networks, a lot of tweaking and optimising is still required. The M2MSAT project, funded by the European space Agency (ESA) is contributing to fill this gap, investigating optimisations for MQTT and CoAP, identified as IoT Application Protocols suitable for IoT data collection over satellite. This work outlines the efficient configuration of MQTT and CoAP in an integrated M2M-Satellite network, and presents some optimisations, designed taking into account the peculiarities of satellite links. [less ▲]

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

in Proceedings of IEEE International Conference on Vehicular Electronics and Safety (ICVES) (ICVES 2018) (2018, September)

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 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 detailUsing mobile phone data for urban network state estimation
Derrmann, Thierry; Frank, Raphaël UL; Engel, Thomas UL et al

Scientific Conference (2018, June)

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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 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 detailPoster: Performance Evaluation of an Open-Source Audio-Video Bridging/Time-Sensitive Networking Testbed for Automotive Ethernet
Xu, Teng Andrea; Adamsky, Florian UL; Turcanu, Ion UL et al

Poster (2018)

Automotive Ethernet (AE) is becoming more and more relevant to the automotive industry due to its support of emerging in-car applications, which have high bandwidth demands and stringent requirements in ... [more ▼]

Automotive Ethernet (AE) is becoming more and more relevant to the automotive industry due to its support of emerging in-car applications, which have high bandwidth demands and stringent requirements in terms of latency and time synchronization. One of the standards under consideration for AE is IEEE 802.1 Audio Video Bridging (AVB)/Time Sensitive Networking (TSN) that provides deterministic data link layer and bounded latency to real-time traffic classes. So far, this protocol stack has only been evaluated using either simulations or proprietary and expensive platforms. In this paper, we design a real testbed system for AE using general-purpose single-board computers and conduct experiments to assess the real-time performance of an open-source AVB/TSN implementation. Our preliminary results show that even under heavy load, AVB/TSN can fulfil the latency requirements of AE while keeping a constant latency variation. [less ▲]

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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 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 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 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 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 ▲]

Detailed reference viewed: 221 (17 UL)