@article{KrentzMeinel2018, author = {Krentz, Konrad-Felix and Meinel, Christoph}, title = {Denial-of-sleep defenses for IEEE 802.15.4 coordinated sampled listening (CSL)}, series = {Computer Networks}, volume = {148}, journal = {Computer Networks}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1389-1286}, doi = {10.1016/j.comnet.2018.10.021}, pages = {60 -- 71}, year = {2018}, abstract = {Coordinated sampled listening (CSL) is a standardized medium access control protocol for IEEE 80215.4 networks. Unfortunately, CSL comes without any protection against so-called denial-of-sleep attacks. Such attacks deprive energy-constrained devices of entering low-power sleep modes, thereby draining their charge. Repercussions of denial-of-sleep attacks include long outages, violated quality-of-service guarantees, and reduced customer satisfaction. However, while CSL has no built-in denial-of-sleep defenses, there already exist denial-of-sleep defenses for a predecessor of CSL, namely ContikiMAC. In this paper, we make two main contributions. First, motivated by the fact that CSL has many advantages over ContikiMAC, we tailor the existing denial-of-sleep defenses for ContikiMAC to CSL. Second, we propose several security enhancements to these existing denial-of-sleep defenses. In effect, our denial-of-sleep defenses for CSL mitigate denial-of-sleep attacks significantly better, as well as protect against a larger range of denial-of-sleep attacks than the existing denial-of-sleep defenses for ContikiMAC. We show the soundness of our denial-of-sleep defenses for CSL both analytically, as well as empirically using a whole new implementation of CSL. (C) 2018 Elsevier B.V. All rights reserved.}, language = {en} } @article{LindbergMeinelWagner2011, author = {Lindberg, Tilmann and Meinel, Christoph and Wagner, Ralf}, title = {Design thinking : a fruitful concept for IT development?}, isbn = {978-3-642-13756-3}, year = {2011}, language = {en} } @article{MeinelLeifer2012, author = {Meinel, Christoph and Leifer, Larry}, title = {Design thinking research}, isbn = {978-3-642-31990-7}, year = {2012}, language = {en} } @article{MeinelLeifer2011, author = {Meinel, Christoph and Leifer, Larry}, title = {Design thinking research}, isbn = {978-3-642-13756-3}, year = {2011}, language = {en} } @article{MeinelLeifer2012, author = {Meinel, Christoph and Leifer, Larry}, title = {Design thinking research}, year = {2012}, language = {en} } @article{MeinelGayvoronskayaMuehle2019, author = {Meinel, Christoph and Gayvoronskaya, Tatiana and M{\"u}hle, Alexander}, title = {Die Zukunftspotenziale der Blockchain-Technologie}, series = {Die Zukunft der Medizin : disruptive Innovationen revolutionieren Medizin und Gesundheit}, journal = {Die Zukunft der Medizin : disruptive Innovationen revolutionieren Medizin und Gesundheit}, publisher = {Medizinisch Wissenschaftliche Verlagsgesellschaft}, address = {Berlin}, isbn = {978-3-95466-398-9}, pages = {259 -- 280}, year = {2019}, language = {de} } @article{AzodiChengMeinel2015, author = {Azodi, Amir and Cheng, Feng and Meinel, Christoph}, title = {Event Driven Network Topology Discovery and Inventory Listing Using REAMS}, series = {Wireless personal communications : an international journal}, volume = {94}, journal = {Wireless personal communications : an international journal}, publisher = {Springer}, address = {New York}, issn = {0929-6212}, doi = {10.1007/s11277-015-3061-3}, pages = {415 -- 430}, year = {2015}, abstract = {Network Topology Discovery and Inventory Listing are two of the primary features of modern network monitoring systems (NMS). Current NMSs rely heavily on active scanning techniques for discovering and mapping network information. Although this approach works, it introduces some major drawbacks such as the performance impact it can exact, specially in larger network environments. As a consequence, scans are often run less frequently which can result in stale information being presented and used by the network monitoring system. Alternatively, some NMSs rely on their agents being deployed on the hosts they monitor. In this article, we present a new approach to Network Topology Discovery and Network Inventory Listing using only passive monitoring and scanning techniques. The proposed techniques rely solely on the event logs produced by the hosts and network devices present within a network. Finally, we discuss some of the advantages and disadvantages of our approach.}, language = {en} } @article{JaegerGraupnerPelchenetal.2018, author = {Jaeger, David and Graupner, Hendrik and Pelchen, Chris and Cheng, Feng and Meinel, Christoph}, title = {Fast Automated Processing and Evaluation of Identity Leaks}, series = {International journal of parallel programming}, volume = {46}, journal = {International journal of parallel programming}, number = {2}, publisher = {Springer}, address = {New York}, issn = {0885-7458}, doi = {10.1007/s10766-016-0478-6}, pages = {441 -- 470}, year = {2018}, abstract = {The relevance of identity data leaks on the Internet is more present than ever. Almost every week we read about leakage of databases with more than a million users in the news. Smaller but not less dangerous leaks happen even multiple times a day. The public availability of such leaked data is a major threat to the victims, but also creates the opportunity to learn not only about security of service providers but also the behavior of users when choosing passwords. Our goal is to analyze this data and generate knowledge that can be used to increase security awareness and security, respectively. This paper presents a novel approach to the processing and analysis of a vast majority of bigger and smaller leaks. We evolved from a semi-manual to a fully automated process that requires a minimum of human interaction. Our contribution is the concept and a prototype implementation of a leak processing workflow that includes the extraction of digital identities from structured and unstructured leak-files, the identification of hash routines and a quality control to ensure leak authenticity. By making use of parallel and distributed programming, we are able to make leaks almost immediately available for analysis and notification after they have been published. Based on the data collected, this paper reveals how easy it is for criminals to collect lots of passwords, which are plain text or only weakly hashed. We publish those results and hope to increase not only security awareness of Internet users but also security on a technical level on the service provider side.}, language = {en} } @article{RezaeiNaeppiLippertetal.2020, author = {Rezaei, Mina and N{\"a}ppi, Janne J. and Lippert, Christoph and Meinel, Christoph and Yoshida, Hiroyuki}, title = {Generative multi-adversarial network for striking the right balance in abdominal image segmentation}, series = {International journal of computer assisted radiology and surgery}, volume = {15}, journal = {International journal of computer assisted radiology and surgery}, number = {11}, publisher = {Springer}, address = {Berlin}, issn = {1861-6410}, doi = {10.1007/s11548-020-02254-4}, pages = {1847 -- 1858}, year = {2020}, abstract = {Purpose: The identification of abnormalities that are relatively rare within otherwise normal anatomy is a major challenge for deep learning in the semantic segmentation of medical images. The small number of samples of the minority classes in the training data makes the learning of optimal classification challenging, while the more frequently occurring samples of the majority class hamper the generalization of the classification boundary between infrequently occurring target objects and classes. In this paper, we developed a novel generative multi-adversarial network, called Ensemble-GAN, for mitigating this class imbalance problem in the semantic segmentation of abdominal images. Method: The Ensemble-GAN framework is composed of a single-generator and a multi-discriminator variant for handling the class imbalance problem to provide a better generalization than existing approaches. The ensemble model aggregates the estimates of multiple models by training from different initializations and losses from various subsets of the training data. The single generator network analyzes the input image as a condition to predict a corresponding semantic segmentation image by use of feedback from the ensemble of discriminator networks. To evaluate the framework, we trained our framework on two public datasets, with different imbalance ratios and imaging modalities: the Chaos 2019 and the LiTS 2017. Result: In terms of the F1 score, the accuracies of the semantic segmentation of healthy spleen, liver, and left and right kidneys were 0.93, 0.96, 0.90 and 0.94, respectively. The overall F1 scores for simultaneous segmentation of the lesions and liver were 0.83 and 0.94, respectively. Conclusion: The proposed Ensemble-GAN framework demonstrated outstanding performance in the semantic segmentation of medical images in comparison with other approaches on popular abdominal imaging benchmarks. The Ensemble-GAN has the potential to segment abdominal images more accurately than human experts.}, language = {en} } @article{RoschkeChengMeinel2013, author = {Roschke, Sebastian and Cheng, Feng and Meinel, Christoph}, title = {High-quality attack graph-based IDS correlation}, series = {Logic journal of the IGPL}, volume = {21}, journal = {Logic journal of the IGPL}, number = {4}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {1367-0751}, doi = {10.1093/jigpal/jzs034}, pages = {571 -- 591}, year = {2013}, abstract = {Intrusion Detection Systems are widely deployed in computer networks. As modern attacks are getting more sophisticated and the number of sensors and network nodes grow, the problem of false positives and alert analysis becomes more difficult to solve. Alert correlation was proposed to analyse alerts and to decrease false positives. Knowledge about the target system or environment is usually necessary for efficient alert correlation. For representing the environment information as well as potential exploits, the existing vulnerabilities and their Attack Graph (AG) is used. It is useful for networks to generate an AG and to organize certain vulnerabilities in a reasonable way. In this article, a correlation algorithm based on AGs is designed that is capable of detecting multiple attack scenarios for forensic analysis. It can be parameterized to adjust the robustness and accuracy. A formal model of the algorithm is presented and an implementation is tested to analyse the different parameters on a real set of alerts from a local network. To improve the speed of the algorithm, a multi-core version is proposed and a HMM-supported version can be used to further improve the quality. The parallel implementation is tested on a multi-core correlation platform, using CPUs and GPUs.}, language = {en} } @article{ThienenNoweskiRauthetal.2012, author = {Thienen, Julia von and Noweski, Christine and Rauth, Ingo and Meinel, Christoph and Lange, Sabine}, title = {If you want to know who are, tell me where you are : the importance of places}, year = {2012}, language = {en} } @article{WangYangMeinel2018, author = {Wang, Cheng and Yang, Haojin and Meinel, Christoph}, title = {Image Captioning with Deep Bidirectional LSTMs and Multi-Task Learning}, series = {ACM transactions on multimedia computing, communications, and applications}, volume = {14}, journal = {ACM transactions on multimedia computing, communications, and applications}, number = {2}, publisher = {Association for Computing Machinery}, address = {New York}, issn = {1551-6857}, doi = {10.1145/3115432}, pages = {20}, year = {2018}, abstract = {Generating a novel and descriptive caption of an image is drawing increasing interests in computer vision, natural language processing, and multimedia communities. In this work, we propose an end-to-end trainable deep bidirectional LSTM (Bi-LSTM (Long Short-Term Memory)) model to address the problem. By combining a deep convolutional neural network (CNN) and two separate LSTM networks, our model is capable of learning long-term visual-language interactions by making use of history and future context information at high-level semantic space. We also explore deep multimodal bidirectional models, in which we increase the depth of nonlinearity transition in different ways to learn hierarchical visual-language embeddings. Data augmentation techniques such as multi-crop, multi-scale, and vertical mirror are proposed to prevent over-fitting in training deep models. To understand how our models "translate" image to sentence, we visualize and qualitatively analyze the evolution of Bi-LSTM internal states over time. The effectiveness and generality of proposed models are evaluated on four benchmark datasets: Flickr8K, Flickr30K, MSCOCO, and Pascal1K datasets. We demonstrate that Bi-LSTM models achieve highly competitive performance on both caption generation and image-sentence retrieval even without integrating an additional mechanism (e.g., object detection, attention model). Our experiments also prove that multi-task learning is beneficial to increase model generality and gain performance. We also demonstrate the performance of transfer learning of the Bi-LSTM model significantly outperforms previous methods on the Pascal1K dataset.}, language = {en} } @article{GruenewaldMeinel2015, author = {Gr{\"u}newald, Franka and Meinel, Christoph}, title = {Implementation and Evaluation of Digital E-Lecture Annotation in Learning Groups to Foster Active Learning}, series = {IEEE transactions on learning technologies}, volume = {8}, journal = {IEEE transactions on learning technologies}, number = {3}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Los Alamitos}, issn = {1939-1382}, doi = {10.1109/TLT.2015.2396042}, pages = {286 -- 298}, year = {2015}, abstract = {The use of video lectures in distance learning involves the two major problems of searchability and active user participation. In this paper, we promote the implementation and usage of a collaborative educational video annotation functionality to overcome these two challenges. Different use cases and requirements, as well as details of the implementation, are explained. Furthermore, we suggest more improvements to foster a culture of participation and an algorithm for the extraction of semantic data. Finally, evaluations in the form of user tests and questionnaires in a MOOC setting are presented. The results of the evaluation are promising, as they indicate not only that students perceive it as useful, but also that the learning effectiveness increases. The combination of personal lecture video annotations with a semantic topic map was also evaluated positively and will thus be investigated further, as will the implementation in a MOOC context.}, language = {en} } @article{AmbassaKayemWolthusenetal.2018, author = {Ambassa, Pacome L. and Kayem, Anne Voluntas dei Massah and Wolthusen, Stephen D. and Meinel, Christoph}, title = {Inferring private user behaviour based on information leakage}, series = {Smart Micro-Grid Systems Security and Privacy}, volume = {71}, journal = {Smart Micro-Grid Systems Security and Privacy}, publisher = {Springer}, address = {Dordrecht}, isbn = {978-3-319-91427-5}, doi = {10.1007/978-3-319-91427-5_7}, pages = {145 -- 159}, year = {2018}, abstract = {In rural/remote areas, resource constrained smart micro-grid (RCSMG) architectures can provide a cost-effective power supply alternative in cases when connectivity to the national power grid is impeded by factors such as load shedding. RCSMG architectures can be designed to handle communications over a distributed lossy network in order to minimise operation costs. However, due to the unreliable nature of lossy networks communication data can be distorted by noise additions that alter the veracity of the data. In this chapter, we consider cases in which an adversary who is internal to the RCSMG, deliberately distorts communicated data to gain an unfair advantage over the RCSMG's users. The adversary's goal is to mask malicious data manipulations as distortions due to additive noise due to communication channel unreliability. Distinguishing malicious data distortions from benign distortions is important in ensuring trustworthiness of the RCSMG. Perturbation data anonymisation algorithms can be used to alter transmitted data to ensure that adversarial manipulation of the data reveals no information that the adversary can take advantage of. However, because existing data perturbation anonymisation algorithms operate by using additive noise to anonymise data, using these algorithms in the RCSMG context is challenging. This is due to the fact that distinguishing benign noise additions from malicious noise additions is a difficult problem. In this chapter, we present a brief survey of cases of privacy violations due to inferences drawn from observed power consumption patterns in RCSMGs centred on inference, and propose a method of mitigating these risks. The lesson here is that while RCSMGs give users more control over power management and distribution, good anonymisation is essential to protecting personal information on RCSMGs.}, language = {en} } @article{RafieevonLoewisMeinel2012, author = {Rafiee, Hosnieh and von Loewis, Martin and Meinel, Christoph}, title = {IPv6 Deployment and Spam Challenges}, series = {IEEE Internet computing}, volume = {16}, journal = {IEEE Internet computing}, number = {6}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Los Alamitos}, issn = {1089-7801}, pages = {22 -- 29}, year = {2012}, abstract = {Spam has posed a serious problem for users of email since its infancy. Today, automated strategies are required to deal with the massive amount of spam traffic. IPv4 networks offer a variety of solutions to reduce spam, but IPv6 networks' large address space and use of temporary addresses - both of which are particularly vulnerable to spam attacks - makes dealing with spam and the use of automated approaches much more difficult. IPv6 thus poses a unique security issue for ISPs because it's more difficult for them to differentiate between good IP addresses and those that are known to originate spam messages.}, language = {en} } @article{ChujfiLaRocheMeinel2017, author = {Chujfi-La-Roche, Salim and Meinel, Christoph}, title = {Matching cognitively sympathetic individual styles to develop collective intelligence in digital communities}, series = {AI \& society : the journal of human-centred systems and machine intelligence}, volume = {35}, journal = {AI \& society : the journal of human-centred systems and machine intelligence}, number = {1}, publisher = {Springer}, address = {New York}, issn = {0951-5666}, doi = {10.1007/s00146-017-0780-x}, pages = {5 -- 15}, year = {2017}, abstract = {Creation, collection and retention of knowledge in digital communities is an activity that currently requires being explicitly targeted as a secure method of keeping intellectual capital growing in the digital era. In particular, we consider it relevant to analyze and evaluate the empathetic cognitive personalities and behaviors that individuals now have with the change from face-to-face communication (F2F) to computer-mediated communication (CMC) online. This document proposes a cyber-humanistic approach to enhance the traditional SECI knowledge management model. A cognitive perception is added to its cyclical process following design thinking interaction, exemplary for improvement of the method in which knowledge is continuously created, converted and shared. In building a cognitive-centered model, we specifically focus on the effective identification and response to cognitive stimulation of individuals, as they are the intellectual generators and multiplicators of knowledge in the online environment. Our target is to identify how geographically distributed-digital-organizations should align the individual's cognitive abilities to promote iteration and improve interaction as a reliable stimulant of collective intelligence. The new model focuses on analyzing the four different stages of knowledge processing, where individuals with sympathetic cognitive personalities can significantly boost knowledge creation in a virtual social system. For organizations, this means that multidisciplinary individuals can maximize their extensive potential, by externalizing their knowledge in the correct stage of the knowledge creation process, and by collaborating with their appropriate sympathetically cognitive remote peers.}, language = {en} } @article{SerthStaubitzvanEltenetal.2022, author = {Serth, Sebastian and Staubitz, Thomas and van Elten, Martin and Meinel, Christoph}, title = {Measuring the effects of course modularizations in online courses for life-long learners}, series = {Frontiers in Education}, volume = {7}, journal = {Frontiers in Education}, editor = {Gamage, Dilrukshi}, publisher = {Frontiers}, address = {Lausanne, Schweiz}, issn = {2504-284X}, doi = {10.3389/feduc.2022.1008545}, pages = {15}, year = {2022}, abstract = {Many participants in Massive Open Online Courses are full-time employees seeking greater flexibility in their time commitment and the available learning paths. We recently addressed these requirements by splitting up our 6-week courses into three 2-week modules followed by a separate exam. Modularizing courses offers many advantages: Shorter modules are more sustainable and can be combined, reused, and incorporated into learning paths more easily. Time flexibility for learners is also improved as exams can now be offered multiple times per year, while the learning content is available independently. In this article, we answer the question of which impact this modularization has on key learning metrics, such as course completion rates, learning success, and no-show rates. Furthermore, we investigate the influence of longer breaks between modules on these metrics. According to our analysis, course modules facilitate more selective learning behaviors that encourage learners to focus on topics they are the most interested in. At the same time, participation in overarching exams across all modules seems to be less appealing compared to an integrated exam of a 6-week course. While breaks between the modules increase the distinctive appearance of individual modules, a break before the final exam further reduces initial interest in the exams. We further reveal that participation in self-paced courses as a preparation for the final exam is unlikely to attract new learners to the course offerings, even though learners' performance is comparable to instructor-paced courses. The results of our long-term study on course modularization provide a solid foundation for future research and enable educators to make informed decisions about the design of their courses.}, language = {en} } @article{TakounaSachsMeinel2014, author = {Takouna, Ibrahim and Sachs, Kai and Meinel, Christoph}, title = {Multiperiod robust optimization for proactive resource provisioning in virtualized data centers}, series = {The journal of supercomputing : an internat. journal of supercomputer design, analysis and use}, volume = {70}, journal = {The journal of supercomputing : an internat. journal of supercomputer design, analysis and use}, number = {3}, publisher = {Springer}, address = {Dordrecht}, issn = {0920-8542}, doi = {10.1007/s11227-014-1246-2}, pages = {1514 -- 1536}, year = {2014}, language = {en} } @article{LindbergKoeppenRauthetal.2012, author = {Lindberg, Tilmann and K{\"o}ppen, Eva and Rauth, Ingo and Meinel, Christoph}, title = {On the perection, adoption and Implementation of design thinking in the IT industry}, year = {2012}, language = {en} } @article{KayemWolthusenMeinel2018, author = {Kayem, Anne Voluntas dei Massah and Wolthusen, Stephen D. and Meinel, Christoph}, title = {Power Systems}, series = {Smart Micro-Grid Systems Security and Privacy}, volume = {71}, journal = {Smart Micro-Grid Systems Security and Privacy}, publisher = {Springer}, address = {Dordrecht}, isbn = {978-3-319-91427-5}, doi = {10.1007/978-3-319-91427-5_1}, pages = {1 -- 8}, year = {2018}, abstract = {Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures, to highly automated management, with current energy provisioning systems being run as cyber-physical systems. Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability, but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour.}, language = {en} }