References of "Engel, Thomas 50001752"
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See detailPOSTER: Traffic Splitting to Counter Website Fingerprinting
de La Cadena Ramos, Augusto Wladimir UL; Mitseva, Asya UL; Pennekamp, Jan et al

Poster (2019, November 11)

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See detailVPGA: an SDN-based Location Privacy Zones Placement Scheme for Vehicular Networks
Boualouache, Abdelwahab UL; Soua, Ridha UL; Engel, Thomas UL

in 38th IEEE International Performance Computing and Communications Conference (IPCCC) (2019, October 29)

Making personal data anonymous is crucial to ensure the adoption of connected vehicles. One of the privacy-sensitive information is location, which once revealed can be used by adversaries to track ... [more ▼]

Making personal data anonymous is crucial to ensure the adoption of connected vehicles. One of the privacy-sensitive information is location, which once revealed can be used by adversaries to track drivers during their journey. Vehicular Location Privacy Zones (VLPZs) is a promising approach to ensure unlinkability. These logical zones can be easily deployed over roadside infrastructures (RIs) such as gas station or electric charging stations. However, the placement optimization problem of VLPZs is NP-hard and thus an efficient allocation of VLPZs to these RIs is needed to avoid their overload and the degradation of the QoS provided within theses RIs. This work considers the optimal placement of the VLPZs and proposes a genetic-based algorithm in a software defined vehicular network to ensure minimized trajectory cost of involved vehicles and hence less consumption of their pseudonyms. The analytical evaluation shows that the proposed approach is cost-efficient and ensures a shorter response time. [less ▲]

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See detailSoftwarization of SCADA: Lightweight Statistical SDN-Agents for Anomaly Detection
Rinaldi, Giulia UL; Adamsky, Florian UL; Soua, Ridha UL et al

in 10th International Conference on Networks of the Future (NoF) (2019, October 04)

The increasing connectivity of restricted areas suchas Critical Infrastructures (CIs) raises major security concernsfor Supervisory Control And Data Acquisition (SCADA) systems,which are deployed to ... [more ▼]

The increasing connectivity of restricted areas suchas Critical Infrastructures (CIs) raises major security concernsfor Supervisory Control And Data Acquisition (SCADA) systems,which are deployed to monitor their operation. Given the impor-tance of an early anomaly detection, Intrusion Detection Systems(IDSs) are introduced in SCADA systems to detect malicious ac-tivities as early as possible. Agents or probes form the cornerstoneof any IDS by capturing network packets and extracting relevantinformation. However, IDSs are facing unprecedented challengesdue to the escalation in the number, scale and diversity of attacks.Software-Defined Network (SDN) then comes into play and canprovide the required flexibility and scalability. Building on that,we introduce Traffic Agent Controllers (TACs) that monitor SDN-enabled switches via OpenFlow. By using lightweight statisticalmetrics such as Kullback-Leibler Divergence (KLD), we are ableto detect the slightest anomalies, such as stealth port scans, evenin the presence of background traffic. The obtained metrics canalso be used to locate the anomalies with precision over 90%inside a hierarchical network topology. [less ▲]

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See detailSDN-based Pseudonym-Changing Strategy for Privacy Preservation in Vehicular Networks
Boualouache, Abdelwahab UL; Soua, Ridha UL; Engel, Thomas UL

in 15th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob'19) (2019, October)

The pseudonym-changing approach is the de-factolocation privacy solution proposed by security standards toensure that drivers are not tracked during their journey. SeveralPseudonym Changing Strategies ... [more ▼]

The pseudonym-changing approach is the de-factolocation privacy solution proposed by security standards toensure that drivers are not tracked during their journey. SeveralPseudonym Changing Strategies (PCSs) have been proposed tosynchronize Pseudonym Changing Processes (PCPs) between con-nected vehicles. However, most of the existing strategies are static,rigid and do not adapt to the vehicles’ context. In this paper, weexploit the Software Defined Network (SDN) paradigm to proposea context-aware pseudonym changing strategy (SDN-PCS) whereSDN controllers orchestrate the dynamic update of the securityparameters of the PCS. Simulation results demonstrate that SDN-PCS strategy outperforms typical static PCSs to perform efficientPCPs and protect the location privacy of vehicular network users [less ▲]

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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 detailForget the Myth of the Air Gap: Machine Learningfor Reliable Intrusion Detection in SCADA Systems
Lopez Perez, Rocio; Adamsky, Florian UL; Soua, Ridha UL et al

in EAI Endorsed Transactions on Security and Safety (2019)

Since Critical Infrastructures (CIs) use systems and equipment that are separated by long distances,Supervisory Control And Data Acquisition (SCADA) systems are used to monitor their behaviour and to send ... [more ▼]

Since Critical Infrastructures (CIs) use systems and equipment that are separated by long distances,Supervisory Control And Data Acquisition (SCADA) systems are used to monitor their behaviour and to send commands remotely. For a long time, operator of CIs applied the air gap principle, a security strategy that physically isolates the control network from other communication channels. True isolation, however,is difficult nowadays due to the massive spread of connectivity: using open protocols and more connectivity opens new network attacks against CIs. To cope with this dilemma, sophisticated security measures are needed to address malicious intrusions, which are steadily increasing in number and variety. However, traditional Intrusion Detection Systems (IDSs) cannot detect attacks that are not already present in their databases. To this end, we assess in this paper Machine Learning (ML) techniques for anomaly detection in SCADA systems using a real data set collected from a gas pipeline system and provided by the Mississippi State University (MSU).The contribution of this paper is two-fold: 1) The evaluation of four techniques for missing data estimation and two techniques for data normalization, 2) The performances of Support Vector Machine (SVM), Random Forest (RF), Bidirectional Long Short Term Memory (BLSTM) are assessed in terms of accuracy, precision,recall and F1 score for intrusion detection. Two cases are differentiated: binary and categorical classifications.Our experiments reveal that RF and BLSTM detect intrusions effectively, with an F1 score of respectively>99% and>96% [less ▲]

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See detailMultipathing Traffic to Reduce Entry Node Exposure in Onion Routing
Pennekamp, Jan; Hiller, Jens; Reuter, Sebastian et al

Poster (2019)

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See detailExperimental Evaluation of Floating Car Data Collection Protocols in Vehicular Networks
Turcanu, Ion UL; Adamsky, Florian; Engel, Thomas UL

in Experimental Evaluation of Floating Car Data Collection Protocols in Vehicular Networks (2019)

The main objectives of the Intelligent Transportation Systems (ITS) vision is to improve road safety, traffic management, and mobility by enabling cooperative communication among participants. This vision ... [more ▼]

The main objectives of the Intelligent Transportation Systems (ITS) vision is to improve road safety, traffic management, and mobility by enabling cooperative communication among participants. This vision requires the knowledge of the current state of the road traffic, which can be obtained by collecting Floating Car Data (FCD) information using Dedicated Short-Range Communication (DSRC) based on the IEEE 802.11p standard. Most of the existing FCD collection protocols have been evaluated via simulations and mathematical models, while the real-world implications have not been thoroughly investigated. This paper presents an open-source implementation of two state-of-the-art FCD collection algorithms, namely BASELINE and DISCOVER. These algorithms are implemented in an open-source vehicular prototyping platform and validated in a real-world experimental setup. [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 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 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 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 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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