This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-04-25 Creation time: 03-09-51 --- Number of references 16 inproceedings 2016-henze-cloudcom-trinics 2016 12 12 366-370 trinics https://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-henze-cloudcom-trinics.pdf Online IEEE Proceedings of the 2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Luxembourg, Luxembourg en 978-1-5090-1445-3 10.1109/CloudCom.2016.0064 1 MartinHenze DanielKerpen JensHiller MichaelEggert DavidHellmanns ErikMühmer OussamaRenuli HenningMaier ChristianStüble RogerHäußling KlausWehrle inproceedings 2016-henze-wpes-cppl 2016 10 24 99-110 ssiclops https://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-henze-wpes-cppl.pdf Online ACM Proceedings of the 15th Workshop on Privacy in the Electronic Society (WPES), co-located with the 23rd ACM Conference on Computer and Communications Security (CCS), Vienna, Austria en 978-1-4503-4569-9 10.1145/2994620.2994627 1 MartinHenze JensHiller SaschaSchmerling Jan HenrikZiegeldorf KlausWehrle inproceedings 2016-mitseva-ccs-fingerprinting 2016 10 24 1766-1768 https://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-mitseva-ccs-fingerprinting.pdf Online ACM Proceedings of the 23rd ACM Conference on Computer and Communications Security (CCS), Vienna, Austria en 978-1-4503-4139-4 10.1145/2976749.2989054 1 AsyaMitseva AndriyPanchenko FabianLanze MartinHenze KlausWehrle ThomasEngel inproceedings 2016-matzutt-ccs-bitcoin 2016 10 24 1769-1771 mynedata /fileadmin/papers/2016/2016-matzutt-ccs-blockchaincontent.pdf Online ACM Proceedings of the 23rd ACM Conference on Computer and Communications Security (CCS), Vienna, Austria en 978-1-4503-4139-4 10.1145/2976749.2989059 1 RomanMatzutt OliverHohlfeld MartinHenze RobinRawiel Jan HenrikZiegeldorf KlausWehrle inproceedings 2016-ackermann-healthcom-eeg-emotion 2016 9 14 159--164 Automatic emotion recognition is an interdisciplinary research field which deals with the algorithmic detection of human affect, e.g. anger or sadness, from a variety of sources, such as speech or facial gestures. Apart from the obvious usage for industry applications in human-robot interaction, acquiring the emotional state of a person automatically also is of great potential for the health domain, especially in psychology and psychiatry. Here, evaluation of human emotion is often done using oral feedback or questionnaires during doctor-patient sessions. However, this can be perceived as intrusive by the patient. Furthermore, the evaluation can only be done in a non-continuous manner, e.g. once a week during therapy sessions. In contrast, using automatic emotion detection, the affect state of a person can be evaluated in a continuous non-intrusive manner, for example to detect early on-sets of depression. An additional benefit of automatic emotion recognition is the objectivity of such an approach, which is not influenced by the perception of the patient and the doctor. To reach the goal of objectivity, it is important, that the source of the emotion is not easily manipulable, e.g. as in the speech modality. To circumvent this caveat, novel approaches in emotion detection research the potential of using physiological measures, such as galvanic skin sensors or pulse meters. In this paper we outline a way of detecting emotion from brain waves, i.e., EEG data. While EEG allows for a continuous, real-time automatic emotion recognition, it furthermore has the charm of measuring the affect close to the point of emergence: the brain. Using EEG data for emotion detection is nevertheless a challenging task: Which features, EEG channel locations and frequency bands are best suited for is an issue of ongoing research. In this paper we evaluate the use of state of the art feature extraction, feature selection and classification algorithms for EEG emotion classification using data from the de facto standard dataset, DEAP. Moreover, we present results that help choose methods to enhance classification performance while simultaneously reducing computational complexity. /fileadmin/papers/2016/2016-ackermann-healthcom-emorec.pdf http://ieeehealthcom2016.com/ Online IEEE 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) Munich, Germany 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) September 14-17, 2016 en 978-1-5090-3370-6 1 PascalAckermann ChristianKohlschein Jó AgilaBitsch Link KlausWehrle SabinaJeschke article 2015-cheng-piap-jmu JMIR Mhealth Uhealth 2016 7 20 4 3 e88 piap http://mhealth.jmir.org/2016/3/e88/ http://www.ncbi.nlm.nih.gov/pubmed/27439444 Online en 2291-5222 10.2196/mhealth.5284 1 Paula Glenda FerrerCheng Roann MunozRamos Jó AgilaBitsch Link Stephan MichaelJonas TimIx Portia Lynn QuetulioSee KlausWehrle techreport 2016-henze-aib-sensorcloud 2016 7 11 AIB-2016-06 arXiv:1607.03239 [cs.NI] 1--24 sensorcloud fileadmin/papers/2016/2016-henze-aib-sensorcloud.pdf Online Department of Computer Science, RWTH Aachen University

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Department of Computer Science, RWTH Aachen University Technical Report en 0935-3232 MartinHenze RenéHummen RomanMatzutt KlausWehrle inproceedings 2016-serror-wowmom-arq 2016 6 21 koi IEEE online 17th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM 2016), Coimbra, Portugal Coimbra, Portugal en 10.1109/WoWMoM.2016.7523534 1 MartinSerror YulinHu ChristianDombrowski KlausWehrle JamesGross inproceedings 2016-werner-networking-stean 2016 5 17 maki IEEE Proceedings of the 15th International IFIP Networking Conference (NETWORKING'16), Vienna, Austira Vienna, Austria IFIP Networking 2016 17.-19.5.2016 978-3-9018-8283-8 10.1109/IFIPNetworking.2016.7497203 1 MarcWerner JohannesSchwandtke MatthiasHollick OliverHohlfeld TorstenZimmermann KlausWehrle inproceedings 2016-stoffers-pads-memo 2016 5 15 221-232 Best Paper Award Automatic Memoization; Accelerating Parameter Studies; Impure Languages memosim,symbiosys http://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-stoffers-pads-memoization.pdf Online ACM

New York, NY

Proceedings of the 4th ACM SIGSIM/PADS Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS’16), Banff, AB, Canada Banff, AB, Canada en 10.1145/2901378.2901386 1 MirkoStoffers DanielSchemmel OscarSoria Dustmann KlausWehrle inproceedings 2016-zimmermann-remp 2016 5 IEEE Proceedings of the IEEE International Conference on Communications (ICC 2016), Kuala Lumpur, Malaysia Kuala Lumpur, Malaysia ICC 2016 23.-27.5.2016 978-1-4799-6664-6 1938-1883 10.1109/ICC.2016.7510787 1 AlexanderFrömmgen TobiasErbshäuser TorstenZimmermann KlausWehrle AlejandroBuchmann inproceedings 2016-henze-claw-dpc 2016 4 8 130-135 ssiclops /fileadmin/papers/2016/2016-henze-claw-dpc.pdf Online IEEE Proceedings of the Second International Workshop on Legal and Technical Issues in Cloud Computing and Cloud-Supported Internet of Things (CLaw 2016), co-located with the 2016 IEEE International Conference on Cloud Engineering (IC2E 2016), Berlin, Germany en 978-1-5090-3684-4 10.1109/IC2EW.2016.24 1 MartinHenze JensHiller OliverHohlfeld KlausWehrle article 2016-fgcs-henze-iotprivacy Future Generation Computer Systems 2016 3 56 701-718 ipacs https://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-henze-fgcs-iotprivacy.pdf Online Elsevier en 0167-739X 10.1016/j.future.2015.09.016 1 MartinHenze LarsHermerschmidt DanielKerpen RogerHäußling BernhardRumpe KlausWehrle inproceedings 2016-panchenko-ndss-fingerprinting 2016 2 21 The website fingerprinting attack aims to identify the content (i.e., a webpage accessed by a client) of encrypted and anonymized connections by observing patterns of data flows such as packet size and direction. This attack can be performed by a local passive eavesdropper – one of the weakest adversaries in the attacker model of anonymization networks such as Tor. In this paper, we present a novel website fingerprinting attack. Based on a simple and comprehensible idea, our approach outperforms all state-of-the-art methods in terms of classification accuracy while being computationally dramatically more efficient. In order to evaluate the severity of the website fingerprinting attack in reality, we collected the most representative dataset that has ever been built, where we avoid simplified assumptions made in the related work regarding selection and type of webpages and the size of the universe. Using this data, we explore the practical limits of website fingerprinting at Internet scale. Although our novel approach is by orders of magnitude computationally more efficient and superior in terms of detection accuracy, for the first time we show that no existing method – including our own – scales when applied in realistic settings. With our analysis, we explore neglected aspects of the attack and investigate the realistic probability of success for different strategies a real-world adversary may follow. https://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-panchenko-ndss-fingerprinting.pdf https://www.informatik.tu-cottbus.de/~andriy/zwiebelfreunde/ Internet Society Proceedings of the 23rd Annual Network and Distributed System Security Symposium (NDSS '16), February 21-24, 2016, San Diego, CA, USA San Diego, CA, USA February 21-24, 2016 978-1-891562-41-9 10.14722/ndss.2016.23477 1 AndriyPanchenko FabianLanze AndreasZinnen MartinHenze JanPennekamp KlausWehrle ThomasEngel article 2016-kunz-tomacs-horizon ACM Transactions on Modeling and Computer Simulation (TOMACS) 2016 1 26 2 12:1--12:26 The technical evolution of wireless communication technology and the need for accurately modeling these increasingly complex systems causes a steady growth in the complexity of simulation models. At the same time, multi-core systems have become the de facto standard hardware platform. Unfortunately, wireless systems pose a particular challenge for parallel execution due to a tight coupling of network entities in space and time. Moreover, model developers are often domain experts with no in-depth understanding of parallel and distributed simulation. In combination, both aspects severely limit the performance and the efficiency of existing parallelization techniques. We address these challenges by presenting parallel expanded event simulation, a novel modeling paradigm that extends discrete events with durations which span a period in simulated time. The resulting expanded events form the basis for a conservative synchronization scheme that considers overlapping expanded events eligible for parallel processing. We furthermore put these concepts into practice by implementing Horizon, a parallel expanded event simulation framework specifically tailored to the characteristics of multi-core systems. Our evaluation shows that Horizon achieves considerable speedups in synthetic as well as real-world simulation models and considerably outperforms the current state-of-the-art in distributed simulation. Parallel discrete event simulation, Multi-core Systems, Wireless Systems, Simulation Modeling Paradigm, Conservative Synchronization horizon ACM en 10.1145/2832909 1 GeorgKunz MirkoStoffers OlafLandsiedel KlausWehrle JamesGross inproceedings 2016-zimmermann-wons-mirco 2016 1 25-32 maki http://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-zimmermann-wons-mirco.pdf IEEE 12th International Conference on Wireless On-demand Network Systems and Services (WONS), Cortina d'Ampezzo, Italy Cortina d'Ampezzo, Italy 12th International Conference on Wireless On-demand Network Systems and Services (WONS) January 20 - 22 2016 en 978-3-901882-80-7 1 TorstenZimmermann JanRüth HannoWirtz KlausWehrle