@proceedings{3874, editor = {{Scheideler, Christian and Fineman, Jeremy T.}}, isbn = {{978-1-4503-5799-9}}, location = {{Vienna, Austria}}, publisher = {{ACM}}, title = {{{Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures}}}, year = {{2018}}, } @inproceedings{2965, author = {{Blömer, Johannes and Löken, Nils}}, booktitle = {{Proceedings of the 13th International Conference on Availability, Reliability and Security, ARES 2018}}, isbn = {{978-1-4503-6448-5}}, location = {{Hamburg, Germany}}, pages = {{25:1----25:10}}, publisher = {{ACM}}, title = {{{Cloud Architectures for Searchable Encryption}}}, doi = {{10.1145/3230833.3230853}}, year = {{2018}}, } @inproceedings{3105, author = {{Derler, David and Jager, Tibor and Slamanig, Daniel and Striecks, Christoph}}, booktitle = {{Advances in Cryptology - EUROCRYPT 2018 - 37th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Tel Aviv, Israel, April 29 - May 3, 2018 Proceedings, Part III}}, pages = {{425----455}}, title = {{{Bloom Filter Encryption and Applications to Efficient Forward-Secret 0-RTT Key Exchange}}}, doi = {{10.1007/978-3-319-78372-7_14}}, year = {{2018}}, } @article{3152, abstract = {{To adapt to continuously changing workloads in networks, components of the running network services may need to be replicated (scaling the network service) and allocated to physical resources (placement) dynamically, also necessitating dynamic re-routing of flows between service components. In this paper, we propose JASPER, a fully automated approach to jointly optimizing scaling, placement, and routing for complex network services, consisting of multiple (virtualized) components. JASPER handles multiple network services that share the same substrate network; services can be dynamically added or removed and dynamic workload changes are handled. Our approach lets service designers specify their services on a high level of abstraction using service templates. JASPER automatically makes scaling, placement and routing decisions, enabling quick reaction to changes. We formalize the problem, analyze its complexity, and develop two algorithms to solve it. Extensive empirical results show the applicability and effectiveness of the proposed approach.}}, author = {{Dräxler, Sevil and Karl, Holger and Mann, Zoltan Adam}}, journal = {{IEEE Transactions on Network and Service Management}}, publisher = {{IEEE}}, title = {{{JASPER: Joint Optimization of Scaling, Placement, and Routing of Virtual Network Services}}}, doi = {{10.1109/TNSM.2018.2846572}}, year = {{2018}}, } @article{3153, author = {{Doherty, Simon and Derrick, John and Dongol, Brijesh and Wehrheim, Heike}}, journal = {{CoRR}}, title = {{{Causal Linearizability: Compositionality for Partially Ordered Executions}}}, year = {{2018}}, } @unpublished{2711, abstract = {{In recent years, researchers have developed a number of tools to conduct taint analysis of Android applications. While all the respective papers aim at providing a thorough empirical evaluation, comparability is hindered by varying or unclear evaluation targets. Sometimes, the apps used for evaluation are not precisely described. In other cases, authors use an established benchmark but cover it only partially. In yet other cases, the evaluations differ in terms of the data leaks searched for, or lack a ground truth to compare against. All those limitations make it impossible to truly compare the tools based on those published evaluations. We thus present ReproDroid, a framework allowing the accurate comparison of Android taint analysis tools. ReproDroid supports researchers in inferring the ground truth for data leaks in apps, in automatically applying tools to benchmarks, and in evaluating the obtained results. We use ReproDroid to comparatively evaluate on equal grounds the six prominent taint analysis tools Amandroid, DIALDroid, DidFail, DroidSafe, FlowDroid and IccTA. The results are largely positive although four tools violate some promises concerning features and accuracy. Finally, we contribute to the area of unbiased benchmarking with a new and improved version of the open test suite DroidBench.}}, author = {{Pauck, Felix and Bodden, Eric and Wehrheim, Heike}}, booktitle = {{arXiv:1804.02903}}, title = {{{Do Android Taint Analysis Tools Keep their Promises?}}}, year = {{2018}}, } @phdthesis{1138, author = {{Gmyr, Robert}}, publisher = {{Universität Paderborn}}, title = {{{Distributed Algorithms for Overlay Networks and Programmable Matter}}}, doi = {{10.17619/UNIPB/1-265}}, year = {{2018}}, } @inproceedings{1163, abstract = {{In this paper we present two major results: First, we introduce the first self-stabilizing version of a supervised overlay network (as introduced in~\cite{DBLP:conf/ispan/KothapalliS05}) by presenting a self-stabilizing supervised skip ring. Secondly, we show how to use the self-stabilizing supervised skip ring to construct an efficient self-stabilizing publish-subscribe system. That is, in addition to stabilizing the overlay network, every subscriber of a topic will eventually know all of the publications that have been issued so far for that topic. The communication work needed to processes a subscribe or unsubscribe operation is just a constant in a legitimate state, and the communication work of checking whether the system is still in a legitimate state is just a constant on expectation for the supervisor as well as any process in the system. }}, author = {{Feldmann, Michael and Kolb, Christina and Scheideler, Christian and Strothmann, Thim Frederik}}, booktitle = {{Proceedings of the 32nd IEEE International Parallel & Distributed Processing Symposium (IPDPS)}}, keywords = {{Topological Self-stabilization, Supervised Overlay, Publish-Subscribe System}}, location = {{Vancouver}}, publisher = {{IEEE}}, title = {{{Self-Stabilizing Supervised Publish-Subscribe Systems}}}, doi = {{10.1109/IPDPS.2018.00114}}, year = {{2018}}, } @inproceedings{1164, abstract = {{We propose a distributed protocol for a queue, called Skueue, which spreads its data fairly onto multiple processes, avoiding bottlenecks in high throughput scenarios. Skueuecan be used in highly dynamic environments, through the addition of join and leave requests to the standard queue operations enqueue and dequeue. Furthermore Skueue satisfies sequential consistency in the asynchronous message passing model. Scalability is achieved by aggregating multiple requests to a batch, which can then be processed in a distributed fashion without hurting the queue semantics. Operations in Skueue need a logarithmic number of rounds w.h.p. until they are processed, even under a high rate of incoming requests.}}, author = {{Feldmann, Michael and Scheideler, Christian and Setzer, Alexander}}, booktitle = {{Proceedings of the 32nd IEEE International Parallel & Distributed Processing Symposium (IPDPS)}}, location = {{Vancouver}}, publisher = {{IEEE}}, title = {{{Skueue: A Scalable and Sequentially Consistent Distributed Queue}}}, doi = {{10.1109/IPDPS.2018.00113}}, year = {{2018}}, } @unpublished{1165, author = {{Witschen, Linus Matthias and Wiersema, Tobias and Platzner, Marco}}, booktitle = {{4th Workshop On Approximate Computing (WAPCO 2018)}}, title = {{{Making the Case for Proof-carrying Approximate Circuits}}}, year = {{2018}}, } @inproceedings{2109, abstract = {{In multinomial classification, reduction techniques are commonly used to decompose the original learning problem into several simpler problems. For example, by recursively bisecting the original set of classes, so-called nested dichotomies define a set of binary classification problems that are organized in the structure of a binary tree. In contrast to the existing one-shot heuristics for constructing nested dichotomies and motivated by recent work on algorithm configuration, we propose a genetic algorithm for optimizing the structure of such dichotomies. A key component of this approach is the proposed genetic representation that facilitates the application of standard genetic operators, while still supporting the exchange of partial solutions under recombination. We evaluate the approach in an extensive experimental study, showing that it yields classifiers with superior generalization performance.}}, author = {{Wever, Marcel Dominik and Mohr, Felix and Hüllermeier, Eyke}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018}}, keywords = {{Classification, Hierarchical Decomposition, Indirect Encoding}}, location = {{Kyoto, Japan}}, publisher = {{ACM}}, title = {{{Ensembles of Evolved Nested Dichotomies for Classification}}}, doi = {{10.1145/3205455.3205562}}, year = {{2018}}, } @inproceedings{17345, author = {{Spalazzese, Romina and Platenius, Marie C. and Becker, Steffen and Engels, Gregor}}, booktitle = {{2018 IEEE International Conference on Software Architecture Companion (ICSA-C)}}, isbn = {{9781538665855}}, title = {{{IoT-ASAP 2018: Message from the Chairs}}}, doi = {{10.1109/icsa-c.2018.00009}}, year = {{2018}}, } @inproceedings{17651, abstract = {{Consider mitigating the effects of denial of service or of malicious traffic in networks by deleting edges. Edge deletion reduces the DoS or the number of the malicious flows, but it also inadvertently removes some of the desired flows. To model this important problem, we formulate two problems: (1) remove all the undesirable flows while minimizing the damage to the desirable ones and (2) balance removing the undesirable flows and not removing too many of the desirable flows. We prove these problems are equivalent to important theoretical problems, thereby being important not only practically but also theoretically, and very hard to approximate in a general network. We employ reductions to nonetheless approximate the problem and also provide a greedy approximation. When the network is a tree, the problems are still MAX SNP-hard, but we provide a greedy-based 2l-approximation algorithm, where l is the longest desirable flow. We also provide an algorithm, approximating the first and the second problem within {\$}{\$}2 {\backslash}sqrt{\{} 2{\backslash}left| E {\backslash}right| {\}}{\$}{\$}and {\$}{\$}2 {\backslash}sqrt{\{}2 ({\backslash}left| E {\backslash}right| + {\backslash}left| {\backslash}text {\{}undesirable flows{\}} {\backslash}right| ){\}}{\$}{\$}, respectively, where E is the set of the edges of the network. We also provide a fixed-parameter tractable (FPT) algorithm. Finally, if the tree has a root such that every flow in the tree flows on the path from the root to a leaf, we solve the problem exactly using dynamic programming.}}, author = {{Polevoy, Gleb and Trajanovski, Stojan and Grosso, Paola and de Laat, Cees}}, booktitle = {{Combinatorial Optimization and Applications}}, editor = {{Kim, Donghyun and Uma, R. N. and Zelikovsky, Alexander}}, isbn = {{978-3-030-04651-4}}, keywords = {{flow, Red-Blue Set Cover, Positive-Negative Partial Set Cover, approximation, tree, MAX SNP-hard, root, leaf, dynamic programming, FPT}}, pages = {{217--232}}, publisher = {{Springer International Publishing}}, title = {{{Removing Undesirable Flows by Edge Deletion}}}, year = {{2018}}, } @article{17666, abstract = {{Software Defined Networks (SDN) and Network Function Virtualisation (NFV) provide the basis for autonomous response and mitigation against attacks on networked computer infrastructures. We propose a new framework that uses SDNs and NFV to achieve this goal: Secure Autonomous Response Network (SARNET). In a SARNET, an agent running a control loop constantly assesses the security state of the network by means of observables. The agent reacts to and resolves security problems, while learning from its previous decisions. Two main metrics govern the decision process in a SARNET: impact and efficiency; these metrics can be used to compare and evaluate countermeasures and are the building blocks for self-learning SARNETs that exhibit autonomous response. In this paper we present the software implementation of the SARNET framework, evaluate it in a real-life network and discuss the tradeoffs between parameters used by the SARNET agent and the efficiency of its actions.}}, author = {{Koning, R. and de Graaff, B. and Polevoy, Gleb and Meijer, R. and de Laat, C. and Grosso, P.}}, issn = {{0167-739X}}, journal = {{Future Generation Computer Systems}}, keywords = {{Software defined networks, Network function virtualization, Cyber attacks, Cyber security, Defense efficiency, Overlay networks}}, title = {{{Measuring the efficiency of SDN mitigations against attacks on computer infrastructures}}}, doi = {{https://doi.org/10.1016/j.future.2018.08.011}}, year = {{2018}}, } @unpublished{17713, author = {{Wever, Marcel Dominik and Mohr, Felix and Hüllermeier, Eyke}}, publisher = {{Arxiv}}, title = {{{Automated Multi-Label Classification based on ML-Plan}}}, year = {{2018}}, } @unpublished{17714, author = {{Mohr, Felix and Wever, Marcel Dominik and Hüllermeier, Eyke}}, title = {{{Automated machine learning service composition}}}, year = {{2018}}, } @inproceedings{1910, abstract = {{Today, model-driven approaches are a cornerstone in modern software development. The Eclipse Modeling Framework (EMF) is highly adopted in practice and generates Java code from platform-independent models with embedded Object Constraint Language (OCL) expressions. However, applications that target multiple platforms like Android, iOS, Windows, web browsers usually need to be implemented in different programming languages. Feature-complete Ecore and OCL runtime APIs are not available for all these platforms, such that their functionality has to be re-implemented. In this paper, we present CrossEcore: A multi-platform enabled modeling framework that generates C#, Swift, TypeScript, and JavaScript code from Ecore models with embedded OCL. An OCL compiler translates OCL expressions into expressions of the target language. The Ecore and OCL API can be consistently used across platforms, which facilitates application portability. CrossEcore is also extendible and can be easily adopted for new programming languages.}}, author = {{Schwichtenberg, Simon and Jovanovikj, Ivan and Gerth, Christian and Engels, Gregor}}, booktitle = {{Proceedings of the 40th International Conference on Software Engineering, ICSE 2018 - Companion Volume}}, location = {{Gothenburg, Sweden}}, title = {{{Poster: CrossEcore: An Extendible Framework to Use Ecore and OCL across Platforms}}}, year = {{2018}}, } @inproceedings{20530, author = {{Bodden, Eric and Nguyen Quang Do, Lisa}}, booktitle = {{Software Engineering und Software Management 2018, Fachtagung des GI-Fachbereichs Softwaretechnik, {SE} 2018, 5.-9. M{\"{a}}rz 2018, Ulm, Germany.}}, isbn = {{978-3-88579-673-2}}, pages = {{205--208}}, title = {{{Explainable Static Analysis}}}, year = {{2018}}, } @article{20543, author = {{Nguyen Quang Do, Lisa and Krüger, Stefan and Hill, Patrick and Ali, Karim and Bodden, Eric}}, issn = {{2326-3881}}, journal = {{IEEE Transactions on Software Engineering}}, keywords = {{Debugging, Static analysis, Tools, Computer bugs, Standards, Writing, Encoding, Testing and Debugging, Program analysis, Development tools, Integrated environments, Graphical environments, Usability testing}}, pages = {{1--1}}, title = {{{Debugging Static Analysis}}}, doi = {{10.1109/TSE.2018.2868349}}, year = {{2018}}, } @proceedings{20544, editor = {{Tichy, Matthias and Bodden, Eric and Kuhrmann, Marco and Wagner, Stefan and Steghöfer, Jan-Philipp}}, isbn = {{978-3-88579-673-2}}, publisher = {{Gesellschaft für Informatik}}, title = {{{Software Engineering und Software Management 2018, Fachtagung des GI-Fachbereichs Softwaretechnik, SE 2018, 5.-9. März 2018, Ulm, Germany}}}, volume = {{{P-279}}}, year = {{2018}}, }