303 research outputs found

    Security and Privacy for Modern Wireless Communication Systems

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    The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

    Parallel and Flow-Based High Quality Hypergraph Partitioning

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    Balanced hypergraph partitioning is a classic NP-hard optimization problem that is a fundamental tool in such diverse disciplines as VLSI circuit design, route planning, sharding distributed databases, optimizing communication volume in parallel computing, and accelerating the simulation of quantum circuits. Given a hypergraph and an integer kk, the task is to divide the vertices into kk disjoint blocks with bounded size, while minimizing an objective function on the hyperedges that span multiple blocks. In this dissertation we consider the most commonly used objective, the connectivity metric, where we aim to minimize the number of different blocks connected by each hyperedge. The most successful heuristic for balanced partitioning is the multilevel approach, which consists of three phases. In the coarsening phase, vertex clusters are contracted to obtain a sequence of structurally similar but successively smaller hypergraphs. Once sufficiently small, an initial partition is computed. Lastly, the contractions are successively undone in reverse order, and an iterative improvement algorithm is employed to refine the projected partition on each level. An important aspect in designing practical heuristics for optimization problems is the trade-off between solution quality and running time. The appropriate trade-off depends on the specific application, the size of the data sets, and the computational resources available to solve the problem. Existing algorithms are either slow, sequential and offer high solution quality, or are simple, fast, easy to parallelize, and offer low quality. While this trade-off cannot be avoided entirely, our goal is to close the gaps as much as possible. We achieve this by improving the state of the art in all non-trivial areas of the trade-off landscape with only a few techniques, but employed in two different ways. Furthermore, most research on parallelization has focused on distributed memory, which neglects the greater flexibility of shared-memory algorithms and the wide availability of commodity multi-core machines. In this thesis, we therefore design and revisit fundamental techniques for each phase of the multilevel approach, and develop highly efficient shared-memory parallel implementations thereof. We consider two iterative improvement algorithms, one based on the Fiduccia-Mattheyses (FM) heuristic, and one based on label propagation. For these, we propose a variety of techniques to improve the accuracy of gains when moving vertices in parallel, as well as low-level algorithmic improvements. For coarsening, we present a parallel variant of greedy agglomerative clustering with a novel method to resolve cluster join conflicts on-the-fly. Combined with a preprocessing phase for coarsening based on community detection, a portfolio of from-scratch partitioning algorithms, as well as recursive partitioning with work-stealing, we obtain our first parallel multilevel framework. It is the fastest partitioner known, and achieves medium-high quality, beating all parallel partitioners, and is close to the highest quality sequential partitioner. Our second contribution is a parallelization of an n-level approach, where only one vertex is contracted and uncontracted on each level. This extreme approach aims at high solution quality via very fine-grained, localized refinement, but seems inherently sequential. We devise an asynchronous n-level coarsening scheme based on a hierarchical decomposition of the contractions, as well as a batch-synchronous uncoarsening, and later fully asynchronous uncoarsening. In addition, we adapt our refinement algorithms, and also use the preprocessing and portfolio. This scheme is highly scalable, and achieves the same quality as the highest quality sequential partitioner (which is based on the same components), but is of course slower than our first framework due to fine-grained uncoarsening. The last ingredient for high quality is an iterative improvement algorithm based on maximum flows. In the sequential setting, we first improve an existing idea by solving incremental maximum flow problems, which leads to smaller cuts and is faster due to engineering efforts. Subsequently, we parallelize the maximum flow algorithm and schedule refinements in parallel. Beyond the strive for highest quality, we present a deterministically parallel partitioning framework. We develop deterministic versions of the preprocessing, coarsening, and label propagation refinement. Experimentally, we demonstrate that the penalties for determinism in terms of partition quality and running time are very small. All of our claims are validated through extensive experiments, comparing our algorithms with state-of-the-art solvers on large and diverse benchmark sets. To foster further research, we make our contributions available in our open-source framework Mt-KaHyPar. While it seems inevitable, that with ever increasing problem sizes, we must transition to distributed memory algorithms, the study of shared-memory techniques is not in vain. With the multilevel approach, even the inherently slow techniques have a role to play in fast systems, as they can be employed to boost quality on coarse levels at little expense. Similarly, techniques for shared-memory parallelism are important, both as soon as a coarse graph fits into memory, and as local building blocks in the distributed algorithm

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Undergraduate and Graduate Course Descriptions, 2023 Spring

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    Wright State University undergraduate and graduate course descriptions from Spring 2023

    2014 GREAT Day Program

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    SUNY Geneseo’s Eighth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1008/thumbnail.jp

    Efficient and Side-Channel Resistant Implementations of Next-Generation Cryptography

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    The rapid development of emerging information technologies, such as quantum computing and the Internet of Things (IoT), will have or have already had a huge impact on the world. These technologies can not only improve industrial productivity but they could also bring more convenience to people’s daily lives. However, these techniques have “side effects” in the world of cryptography – they pose new difficulties and challenges from theory to practice. Specifically, when quantum computing capability (i.e., logical qubits) reaches a certain level, Shor’s algorithm will be able to break almost all public-key cryptosystems currently in use. On the other hand, a great number of devices deployed in IoT environments have very constrained computing and storage resources, so the current widely-used cryptographic algorithms may not run efficiently on those devices. A new generation of cryptography has thus emerged, including Post-Quantum Cryptography (PQC), which remains secure under both classical and quantum attacks, and LightWeight Cryptography (LWC), which is tailored for resource-constrained devices. Research on next-generation cryptography is of importance and utmost urgency, and the US National Institute of Standards and Technology in particular has initiated the standardization process for PQC and LWC in 2016 and in 2018 respectively. Since next-generation cryptography is in a premature state and has developed rapidly in recent years, its theoretical security and practical deployment are not very well explored and are in significant need of evaluation. This thesis aims to look into the engineering aspects of next-generation cryptography, i.e., the problems concerning implementation efficiency (e.g., execution time and memory consumption) and security (e.g., countermeasures against timing attacks and power side-channel attacks). In more detail, we first explore efficient software implementation approaches for lattice-based PQC on constrained devices. Then, we study how to speed up isogeny-based PQC on modern high-performance processors especially by using their powerful vector units. Moreover, we research how to design sophisticated yet low-area instruction set extensions to further accelerate software implementations of LWC and long-integer-arithmetic-based PQC. Finally, to address the threats from potential power side-channel attacks, we present a concept of using special leakage-aware instructions to eliminate overwriting leakage for masked software implementations (of next-generation cryptography)

    Easily decoded error correcting codes

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    This thesis is concerned with the decoding aspect of linear block error-correcting codes. When, as in most practical situations, the decoder cost is limited an optimum code may be inferior in performance to a longer sub-optimum code' of the same rate. This consideration is a central theme of the thesis. The best methods available for decoding short optimum codes and long B.C.H. codes are discussed, in some cases new decoding algorithms for the codes are introduced. Hashim's "Nested" codes are then analysed. The method of nesting codes which was given by Hashim is shown to be optimum - but it is seen that the codes are less easily decoded than was previously thought. "Conjoined" codes are introduced. It is shown how two codes with identical numbers of information bits may be "conjoined" to give a code with length and minimum distance equal to the sum of the respective parameters of the constituent codes but with the same number of information bits. A very simple decoding algorithm is given for the codes whereby each constituent codeword is decoded and then a decision is made as to the correct decoding. A technique is given for adding more codewords to conjoined codes without unduly increasing the decoder complexity. Lastly, "Array" codes are described. They are formed by making parity checks over carefully chosen patterns of information bits arranged in a two-dimensional array. Various methods are given for choosing suitable patterns. Some of the resulting codes are self-orthogonal and certain of these have parameters close to the optimum for such codes. A method is given for adding more codewords to array codes, derived from a process of augmentation known for product codes

    Naval Postgraduate School Academic Catalog - February 2023

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    Cybersecurity and Quantum Computing: friends or foes?

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Programs and Courses Catalog 2023-2024

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    Contents: --- Academic Calendar--- Guide to Course Number Prefixes--- Course Number Explanation--- Common Course Numbers--- List of Programs by Department--- General Information--- Academic Regulations--- Academic Structure--- Admission Requirements--- Enrollment and Registration Procedures--- Fees and Financial Aid--- Graduate Information, Admission, Academic Regulations, and Degree Requirements--- Student Life--- The Fine and Performing Arts at UNI--- The University and Its Programs--- Undergraduate Information and Degree Requirements--- University Facilities and Educational Services--- Learning Outcomes--- Plan of Study (4-year plans)--- All Majors--- Business--- Education--- Humanities, Arts and Sciences--- Social and Behavioral Sciences--- Interdisciplinary--- College of Business--- Department of Accounting--- Department of Economics--- Department of Finance--- Department of Management--- Department of Marketing and Entrepreneurship--- College of Education--- Department of Curriculum and Instruction--- Department of Educational Psychology, Foundations, and Leadership Studies--- Department of Health, Recreation and Community Services--- Department of Kinesiology--- Special Education--- Teaching--- College of Humanities, Arts and Sciences--- Department of Applied Engineering & Technical Management--- Department of Art--- Department of Biology--- Department of Chemistry and Biochemistry--- Department of Communication and Media--- Department of Communication Sciences and Disorders--- Department of Computer Science--- Department of Earth and Environmental Sciences--- Iowa Lakeside Laboratory--- Department of Languages and Literatures--- Department of Mathematics--- School of Music--- Department of Philosophy and World Religions--- Department of Physics--- Science Education--- Department of Theatre--- College of Social and Behavioral Sciences--- School of Applied Human Sciences--- Department of Geography--- Department of History--- Department of Military Science--- Department of Political Science--- Department of Psychology--- Department of Social Work--- Department of Sociology, Anthropology, and Criminology--- Social Science--- Interdisciplinary Majors, Minors and Program Certificates--- Bachelor of Applied Science Degree Programs--- Bachelor of Arts Degree and Minor Programs--- Master of Arts Degree Programs--- Program Certificates--- Undergraduate Studies--- Regents Alternative Pathway to Iowa Licensure (RAPIL)https://scholarworks.uni.edu/uni_catalogs/1122/thumbnail.jp
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