Relevant bibliographies by topics / Cyber Algorithm

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Cyber Algorithm'

Author: Grafiati
Published: 30 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Cyber Algorithm"

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Yin, Peng-Yeng, Fred Glover, Manuel Laguna, and Jia-Xian Zhu. "A Complementary Cyber Swarm Algorithm." International Journal of Swarm Intelligence Research 2, no. 2 (April 2011): 22–41. http://dx.doi.org/10.4018/jsir.2011040102.

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A recent study (Yin et al., 2010) showed that combining particle swarm optimization (PSO) with the strategies of scatter search (SS) and path relinking (PR) produces a Cyber Swarm Algorithm that creates a more effective form of PSO than methods that do not incorporate such mechanisms. This paper proposes a Complementary Cyber Swarm Algorithm (C/CyberSA) that performs in the same league as the original Cyber Swarm Algorithm but adopts different sets of ideas from the tabu search (TS) and the SS/PR template. The C/CyberSA exploits the guidance information and restriction information produced in the history of swarm search and the manipulation of adaptive memory. Responsive strategies using long term memory and path relinking implementations are proposed that make use of critical events encountered in the search. Experimental results with a large set of challenging test functions show that the C/CyberSA outperforms two recently proposed swarm-based methods by finding more optimal solutions while simultaneously using a smaller number of function evaluations. The C/CyberSA approach further produces improvements comparable to those obtained by the original CyberSA in relation to the Standard PSO 2007 method (Clerc, 2008).
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Liu, Xin-Rui, Yuan Meng, and Peng Chang. "Node Importance Evaluation of Cyber-Physical System under Cyber-Attacks Spreading." Complexity 2021 (January 16, 2021): 1–15. http://dx.doi.org/10.1155/2021/6641030.

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The study of cyber-attacks, and in particular the spread of attack on the power cyber-physical system, has recently attracted considerable attention. Identifying and evaluating the important nodes under the cyber-attack propagation scenario are of great significance for improving the reliability and survivability of the power system. In this paper, we improve the closeness centrality algorithm and propose a compound centrality algorithm based on adaptive coefficient to evaluate the importance of single-layer network nodes. Moreover, we quantitatively calculated the decouple degree of cascading failures caused by exposed nodes formed by attack propagation. At last, experiments based on the IEEE 57 test system show that the proposed compound centrality algorithm can match the cyber-attack propagation scenario well, and we give the importance values of the nodes in a specific attack scenario.
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Choi, Young Hwan, Ali Sadollah, and Joong Hoon Kim. "Improvement of Cyber-Attack Detection Accuracy from Urban Water Systems Using Extreme Learning Machine." Applied Sciences 10, no. 22 (November 18, 2020): 8179. http://dx.doi.org/10.3390/app10228179.

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This study proposes a novel detection model for the detection of cyber-attacks using remote sensing data on water distribution systems (i.e., pipe flow sensor, nodal pressure sensor, tank water level sensor, and programmable logic controllers) by machine learning approaches. The most commonly used and well-known machine learning algorithms (i.e., k-nearest neighbor, support vector machine, artificial neural network, and extreme learning machine) were compared to determine the one with the best detection performance. After identifying the best algorithm, several improved versions of the algorithm are compared and analyzed according to their characteristics. Their quantitative performances and abilities to correctly classify the state of the urban water system under cyber-attack were measured using various performance indices. Among the algorithms tested, the extreme learning machine (ELM) was found to exhibit the best performance. Moreover, this study not only has identified excellent algorithm among the compared algorithms but also has considered an improved version of the outstanding algorithm. Furthermore, the comparison was performed using various representative performance indices to quantitatively measure the prediction accuracy and select the most appropriate model. Therefore, this study provides a new perspective on the characteristics of various versions of machine learning algorithms and their application to different problems, and this study may be referenced as a case study for future cyber-attack detection fields.
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Yang, Tingting, Hailong Feng, Jian Zhao, Ruilong Deng, Ying Wang, and Zhou Su. "Genetic optimization–based scheduling in maritime cyber physical systems." International Journal of Distributed Sensor Networks 13, no. 7 (July 2017): 155014771771716. http://dx.doi.org/10.1177/1550147717717163.

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In this article, we attempt to solve the issue of optimal scheduling for vessels monitoring video data uploading in maritime cyber physical systems, during the period of sailing from the origin port to destination port. We consider the terrestrial infrastructure-based networking, delivering video packets assisted by the shoreside infostations to the authorities on land. Each video packet has respective elements (i.e. release time, deadline, processing time, and weight) to describe, in which deadline is utilized to demonstrate the time domain limitation before that to upload it successfully. In order to cope with the computation complexity of traditional scheduling algorithms in intermittent infostations scenario, time-capacity mapping method is exploited to transfer it to a continue scenario when classic scheduling algorithms could be utilized with lower time complexity. An ingenious mathematic job-machine scheduling formulation is indicated with the goal of minimizing the total penalties of tardiness of uploaded video packets, taking into account the tardiness and the weights of jobs simultaneously. A genetic based algorithm, as well as an improved genetic algorithm–based optimization scheme, is proposed to target this optimization formulation. Specially, the genetic based algorithm as well as the improved genetic based algorithm are described in detail, including a novel chromosome representation, a heuristic initialization procedure, as well as a modified crossover and mutation process. The effectiveness of the proposed schemes is verified by the simulation results.
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N, Valliammal, and Barani Shaju. "Deep learning algorithm based cyber-attack detection in cyber-physical systems-a survey." International Journal of Advanced Technology and Engineering Exploration 5, no. 49 (December 21, 2018): 489–94. http://dx.doi.org/10.19101/ijatee.2018.547030.

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P, Karunakaran. "Deep Learning Approach to DGA Classification for Effective Cyber Security." December 2020 2, no. 4 (January 6, 2021): 203–13. http://dx.doi.org/10.36548/jucct.2020.4.003.

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In recent years, invaders are increasing rapidly in an internet world. Generally, in order to detect the anonymous attackers algorithm needs more number of features. Many algorithms fail in the efficiency of detection malicious code. Immediately this codes will not infect the system; it will attack server after communicate later. Our research focuses on analyzing the traffic of botnets for the domain name determination to the IP address of the server. This botnet creates the domain name differently. Many domains are generated by attackers and create the huge Domain Name System (DNS) traffic. In this research paper, uses both public and real time environments datasets to detect the text features as well as knowledge based feature extraction. The classifying of Domain Generation Algorithm (DGA) generated malicious domains randomly making the efficiency down in many algorithms which were used preprocessing without proper feature extraction. Effectively, our proposed algorithm is used to detect DGA which generates malicious domains randomly. This effective detection of our proposed algorithm performs with text based label prediction and additional features for extraction to improve the efficiency of the model. Our proposed model achieved 94.9% accuracy for DGA classification with help of additional feature extraction and knowledge based extraction in the deep learning architecture.
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Yin, Peng-Yeng, Po-Yen Chen, Ying-Chieh Wei, and Rong-Fuh Day. "Cyber Firefly Algorithm Based on Adaptive Memory Programming for Global Optimization." Applied Sciences 10, no. 24 (December 15, 2020): 8961. http://dx.doi.org/10.3390/app10248961.

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Recently, two evolutionary algorithms (EAs), the glowworm swarm optimization (GSO) and the firefly algorithm (FA), have been proposed. The two algorithms were inspired by the bioluminescence process that enables the light-mediated swarming behavior for mating or foraging. From our literature survey, we are convinced with much evidence that the EAs can be more effective if appropriate responsive strategies contained in the adaptive memory programming (AMP) domain are considered in the execution. This paper contemplates this line and proposes the Cyber Firefly Algorithm (CFA), which integrates key elements of the GSO and the FA and further proliferates the advantages by featuring the AMP-responsive strategies including multiple guiding solutions, pattern search, multi-start search, swarm rebuilding, and the objective landscape analysis. The robustness of the CFA has been compared against the GSO, FA, and several state-of-the-art metaheuristic methods. The experimental result based on intensive statistical analyses showed that the CFA performs better than the other algorithms for global optimization of benchmark functions.
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Kozik, Rafał, and Michał Choraś. "Pattern Extraction Algorithm for NetFlow-Based Botnet Activities Detection." Security and Communication Networks 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/6047053.

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As computer and network technologies evolve, the complexity of cybersecurity has dramatically increased. Advanced cyber threats have led to current approaches to cyber-attack detection becoming ineffective. Many currently used computer systems and applications have never been deeply tested from a cybersecurity point of view and are an easy target for cyber criminals. The paradigm of security by design is still more of a wish than a reality, especially in the context of constantly evolving systems. On the other hand, protection technologies have also improved. Recently, Big Data technologies have given network administrators a wide spectrum of tools to combat cyber threats. In this paper, we present an innovative system for network traffic analysis and anomalies detection to utilise these tools. The systems architecture is based on a Big Data processing framework, data mining, and innovative machine learning techniques. So far, the proposed system implements pattern extraction strategies that leverage batch processing methods. As a use case we consider the problem of botnet detection by means of data in the form of NetFlows. Results are promising and show that the proposed system can be a useful tool to improve cybersecurity.
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Do, ChoXuan, Nguyen Quang Dam, and Nguyen Tung Lam. "Optimization of network traffic anomaly detection using machine learning." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 3 (June 1, 2021): 2360. http://dx.doi.org/10.11591/ijece.v11i3.pp2360-2370.

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In this paper, to optimize the process of detecting cyber-attacks, we choose to propose 2 main optimization solutions: Optimizing the detection method and optimizing features. Both of these two optimization solutions are to ensure the aim is to increase accuracy and reduce the time for analysis and detection. Accordingly, for the detection method, we recommend using the Random Forest supervised classification algorithm. The experimental results in section 4.1 have proven that our proposal that use the Random Forest algorithm for abnormal behavior detection is completely correct because the results of this algorithm are much better than some other detection algorithms on all measures. For the feature optimization solution, we propose to use some data dimensional reduction techniques such as information gain, principal component analysis, and correlation coefficient method. The results of the research proposed in our paper have proven that to optimize the cyber-attack detection process, it is not necessary to use advanced algorithms with complex and cumbersome computational requirements, it must depend on the monitoring data for selecting the reasonable feature extraction and optimization algorithm as well as the appropriate attack classification and detection algorithms.
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Ma, Wu Bin, Ming Xing Liu, Su Deng, and Hong Bin Huang. "A Spatial Resource Top-K Query Algorithm in Cyber Physical System." Advanced Materials Research 774-776 (September 2013): 1725–28. http://dx.doi.org/10.4028/www.scientific.net/amr.774-776.1725.

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Cyber physical system (CPS) mainly means that the conjoining of information and physical resources. The physical elements, which could be treated as spatial resources, need be queried through information field. The key problem is how to construct spatial resource index structure and accordingly retrieving algorithm. The spatial retrieving algorithm is widely used in the Internet and moving object. The traditional spatial resource retrieving algorithms ignore the uncertain factor of the spatial resource, which is the important feature of the military resource network. This paper use an index structure named BIR-tree, based on the belief of resource, we also propose corresponding efficient and accurate top-k retrieving algorithm. On the base of traditional IR-tree, we define the resource and regional belief aiming at special spatial environment. The results of our empirical studies with an implementation of the proposed algorithm show it is capable of excellent performance.
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Dissertations / Theses on the topic "Cyber Algorithm"

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Thames, John Lane. "Advancing cyber security with a semantic path merger packet classification algorithm." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45872.

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This dissertation investigates and introduces novel algorithms, theories, and supporting frameworks to significantly improve the growing problem of Internet security. A distributed firewall and active response architecture is introduced that enables any device within a cyber environment to participate in the active discovery and response of cyber attacks. A theory of semantic association systems is developed for the general problem of knowledge discovery in data. The theory of semantic association systems forms the basis of a novel semantic path merger packet classification algorithm. The theoretical aspects of the semantic path merger packet classification algorithm are investigated, and the algorithm's hardware-based implementation is evaluated along with comparative analysis versus content addressable memory. Experimental results show that the hardware implementation of the semantic path merger algorithm significantly outperforms content addressable memory in terms of energy consumption and operational timing.
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Chatterjee, Aakriti. "Development of an RSA Algorithm using Reduced RISC V instruction Set." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1617104502129937.

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Roychowdhury, Sayak. "Data-Driven Policies for Manufacturing Systems and Cyber Vulnerability Maintenance." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1493905616531091.

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Guymon, Daniel Wade. "Cyber-physical Algorithms for Enhancing Collaboration." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/31919.

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The research presented in this thesis covers two specific problems within the larger domain of cyber-physical algorithms for enhancing collaboration between one or more people. The two specific problems are 1) determining when people are going to arrive late to a meeting and 2) creating ad-hoc secure pairing protocols for short-range communication. The domain was broken down at opposite extremes in order to derive these problems to work on: 1) collaborations that are planned long in advance and deviations from the plan need to be detected and 2) collaborations that are not planned and need to be dynamically created and secured. Empirical results show the functionality and performance of user late arrival detection for planned collaborations and end-user authentication protocols for unplanned collaborations.
Master of Science
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Gujrati, Sumeet. "Models and algorithms for cyber-physical systems." Diss., Kansas State University, 2013. http://hdl.handle.net/2097/16922.

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Doctor of Philosophy
Department of Computing and Information Sciences
Gurdip Singh
In this dissertation, we propose a cyber-physical system model, and based on this model, present algorithms for a set of distributed computing problems. Our model specifies a cyber-physical system as a combination of cyber-infrastructure, physical-infrastructure, and user behavior specification. The cyber-infrastructure is superimposed on the physical-infrastructure and continuously monitors its (physical-infrastructure's) changing state. Users operate in the physical-infrastructure and interact with the cyber-infrastructure using hand-held devices and sensors; and their behavior is specified in terms of actions they can perform (e.g., move, observe). While in traditional distributed systems, users interact solely via the underlying cyber-infrastructure, users in a cyber-physical system may interact directly with one another, access sensor data directly, and perform actions asynchronously with respect to the underlying cyber-infrastructure. These additional types of interactions have an impact on how distributed algorithms for cyber-physical systems are designed. We augment distributed mutual exclusion and predicate detection algorithms so that they can accommodate user behavior, interactions among them and the physical-infrastructure. The new algorithms have two components - one describing the behavior of the users in the physical-infrastructure and the other describing the algorithms in the cyber-infrastructure. Each combination of users' behavior and an algorithm in the cyber-infrastructure yields a different cyber-physical system algorithm. We have performed extensive simulation study of our algorithms using OMNeT++ simulation engine and Uppaal model checker. We also propose Cyber-Physical System Modeling Language (CPSML) to specify cyber-physical systems, and a centralized global state recording algorithm.
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Furrer, Frank J., and Georg Püschel. "From Algorithmic Computing to Autonomic Computing." Technische Universität Dresden, 2018. https://tud.qucosa.de/id/qucosa%3A30773.

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In algorithmic computing, the program follows a predefined set of rules – the algorithm. The analyst/designer of the program analyzes the intended tasks of the program, defines the rules for its expected behaviour and programs the implementation. The creators of algorithmic software must therefore foresee, identify and implement all possible cases for its behaviour in the future application! However, what if the problem is not fully defined? Or the environment is uncertain? What if situations are too complex to be predicted? Or the environment is changing dynamically? In many such cases algorithmic computing fails. In such situations, the software needs an additional degree of freedom: Autonomy! Autonomy allows software to adapt to partially defined problems, to uncertain or dynamically changing environments and to situations that are too complex to be predicted. As more and more applications – such as autonomous cars and planes, adaptive power grid management, survivable networks, and many more – fall into this category, a gradual switch from algorithmic computing to autonomic computing takes place. Autonomic computing has become an important software engineering discipline with a rich literature, an active research community, and a growing number of applications.:Introduction 5 1 A Process Data Based Autonomic Optimization of Energy Efficiency in Manufacturing Processes, Daniel Höschele 9 2 Eine autonome Optimierung der Stabilität von Produktionsprozessen auf Basis von Prozessdaten, Richard Horn 25 3 Assuring Safety in Autonomous Systems, Christian Rose 41 4 MAPE-K in der Praxis - Grundlage für eine mögliche automatische Ressourcenzuweisung, in der Cloud Michael Schneider 59
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Kem, Oudom. "Modélisation et exploitation des connaissances de l’environnement : une approche multi-agents pour la recherche d’itinéraires multi-objectifs dans des environnements ubiquitaires." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEM023.

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L'utilisation des téléphones intelligents, le recours aux assistants personnels intelligents ou encore le développement des maisons intelligentes sont autant d'exemples illustrant le développement toujours plus rapide de l'informatique ubiquitaire, de l'Internet des objets et de l'intelligence artificielle. Le croisement des résultats issus de ces domaines de recherche contribue à changer notre quotidien et constitue un environnement fertile pour de nouveaux travaux. Ainsi, l’intégration des entités cyber-physiques dans des environnements sociaux de différentes échelles allant des maisons aux villes intelligentes amène de très nombreuses perspectives. Ce changement de paradigme met à notre disposition une énorme quantité d'informations et de services utiles, offrant ainsi la possibilité de traiter les problèmes classiques de manière nouvelle, différente et potentiellement plus efficace. Si les solutions à construire bénéficient de ces possibilités, elles doivent également répondre à de nouvelles contraintes et nouveaux défis. La recherche d’itinéraires multi-objectifs est un sous-cas du problème classique de recherche d'un chemin entre un lieu de départ et une destination auquel s'ajoute la contrainte de passage par un ensemble de lieux permettant de satisfaire un ensemble de buts. L'objectif de cette thèse est de proposer une solution pour la résolution de la recherche d'itinéraires multi-objectifs appliqués aux environnements cyber-physiques tels que les Smart Transits. Dans notre solution, nous avons proposé une méthode fondée sur les technologies du web sémantique pour modéliser de manière intégrée un environnement cyber-physique dans toutes ses dimensions, i.e., cybernétiques, physiques et sociales. Pour la recherche de chemin, nous avons proposé une approche multi-agents, exécutant un algorithme de recherche collaborative et incrémentale, qui utilise les connaissances de l'environnement pour trouver le chemin optimal. Cet algorithme adapte aussi le chemin en prenant en compte la dynamique de l'environnement
From intelligent artificial personal assistants to smart cities, we are experiencing the shifting towards Internet of Things (IoT), ubiquitous computing, and artificial intelligence. Cyber-physical entities are embedded in social environments of various scales from smart homes, to smart airports, to smart cities, and the list continues.This paradigm shift coupled with ceaseless expansion of the Web supplies us with tremendous amount of useful information and services, which creates opportunities for classical problems to be addressed in new, different, and potentially more efficient manners. Along with the new possibilities, we are, at the same time, presented with new constraints, problems, and challenges. Multi-goal pathfinding, a variant of the classical pathfinding, is a problem of finding a path between a start and a destination which also allows a set of goals to be satisfied along the path. The aim of this dissertation is to propose a solution to solve multi-goal pathfinding in ubiquitous environments such as smart transits. In our solution, to provide an abstraction of the environment, we proposed a knowledge model based on the semantic web technologies to describe a ubiquitous environment integrating its cybernetic, physical, and social dimensions. To perform the search, we developed a multi-agent algorithm based on a collaborative and incremental search algorithm that exploits the knowledge of the environment to find the optimal path. The proposed algorithm continuously adapts the path to take into account the dynamics of the environment
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Staub, Nicolas. "Models, algorithms and architectures for cooperative manipulation with aerial and ground robots." Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30169/document.

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Les dernières années ont vu le développement de recherches portant sur l'interaction physique entre les robots aériens et leur environnement, accompagné de l'apparition de nombreux nouveaux systèmes mécaniques et approches de régulation. La communauté centrée autour de la robotique aérienne observe actuellement un déplacement de paradigmes des approches classiques de guidage, de navigation et de régulation vers des tâches moins triviales, telle le développement de l'interaction physique entre robots aériens et leur environnement. Ceci correspond à une extension des tâches dites de manipulation, du sol vers les airs. Cette thèse contribue au domaine de la manipulation aérienne en proposant un nouveau concept appelé MAGMaS, pour " Multiple Aerial Ground Manipulator System ". Les motivations qui ont conduites à l'association de manipulateurs terrestres et aériens pour effectuer des tâches de manipulation coopérative, résident dans une volonté d'exploiter leurs particularités respectives. Les manipulateurs terrestres apportant leur importante force et les manipulateurs aériens apportant leur vaste espace de travail. La première contribution de cette thèse présente une modélisation rigoureuse des MAGMaS. Les propriétés du système ainsi que ses possibles extensions sont discutées. Les méthodes de planning, d'estimation et de régulation nécessaire à l'exploitation des MAGMaS pour des tâches de manipulation collaborative sont dérivées. Ce travail propose d'exploiter les redondances des MAGMaS grâce à un algorithme optimal d'allocation de forces entre les manipulateurs. De plus, une méthode générale d'estimation de forces pour robots aériens est introduite. Toutes les techniques et les algorithmes présentés dans cette thèse sont intégrés dans une architecture globale, utilisée à la fois pour la simulation et la validation expérimentale. Cette architecture est en outre augmentée par l'addition d'une structure de télé-présence, afin de permettre l'opération à distances des MAGMaS. L'architecture générale est validée par une démonstration de levage de barre, qui est une application représentative des potentiels usages des MAGMaS. Une autre contribution relative au développement des MAGMaS consiste en une étude exploratoire de la flexibilité dans les objets manipulés par un MAGMaS. Un modèle du phénomène vibratoire est dérivé afin de mettre en exergue ses propriétés en termes de contrôle. La dernière contribution de cette thèse consiste en une étude exploratoire sur l'usage des actionneurs à raideur variable dans les robots aériens, dotant ces systèmes d'une compliance mécanique intrinsèque et de capacité de stockage d'énergie. Les fondements théoriques sont associés à la synthèse d'un contrôleur non-linéaire. L'approche proposée est validée par le biais d'expériences reposant sur l'intégration d'un actionneur à raideur variable léger sur un robot aérien
In recent years, the subject of physical interaction for aerial robots has been a popular research area with many new mechanical designs and control approaches being proposed. The aerial robotics community is currently observing a paradigm shift from classic guidance, navigation, and control tasks towards more unusual tasks, for example requesting aerial robots to physically interact with the environment, thus extending the manipulation task from the ground into the air. This thesis contributes to the field of aerial manipulation by proposing a novel concept known has Multiple Aerial-Ground Manipulator System or MAGMaS, including what appears to be the first experimental demonstration of a MAGMaS and opening a new route of research. The motivation behind associating ground and aerial robots for cooperative manipulation is to leverage their respective particularities, ground robots bring strength while aerial robots widen the workspace of the system. The first contribution of this work introduces a meticulous system model for MAGMaS. The system model's properties and potential extensions are discussed in this work. The planning, estimation and control methods which are necessary to exploit MAGMaS in a cooperative manipulation tasks are derived. This works proposes an optimal control allocation scheme to exploit the MAGMaS redundancies and a general model-based force estimation method is presented. All of the proposed techniques reported in this thesis are integrated in a global architecture used for simulations and experimental validation. This architecture is extended by the addition of a tele-presence framework to allow remote operations of MAGMaS. The global architecture is validated by robust demonstrations of bar lifting, an application that gives an outlook of the prospective use of the proposed concept of MAGMaS. Another contribution in the development of MAGMaS consists of an exploratory study on the flexibility of manipulated loads. A vibration model is derived and exploited to showcase vibration properties in terms of control. The last contribution of this thesis consists of an exploratory study on the use of elastic joints in aerial robots, endowing these systems with mechanical compliance and energy storage capabilities. Theoretical groundings are associated with a nonlinear controller synthesis. The proposed approach is validated by experimental work which relies on the integration of a lightweight variable stiffness actuator on an aerial robot
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Markwood, Ian. "Offensive and Defensive Security for Everyday Computer Systems." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7336.

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This dissertation treats a variety of topics in the computer security domain which have direct impact on everyday life. The first extends false data injection attacks against state estimation in electric power grids and then provides a novel power flow model camouflage method to hamper these attacks. The second deals with automotive theft response, detailing a method for a car to intelligently identify when it has been stolen, based on collected behavioral traits of its driver. The third demonstrates a new attack against the content integrity of the PDF file format, caus- ing humans and computers to see different information within the same PDF documents. This dissertation lastly describes some future work efforts, identifying some potential vulnerabilities in the automated enforcement of copyright protection for audio (particularly music) in online systems such as YouTube.
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Rukavina, Ivan. "Cyber-physics intrinsic modelling for smart systems." Thesis, Compiègne, 2021. http://bibliotheque.utc.fr/EXPLOITATION/doc/IFD/2021COMP2581.

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Dans le cadre de cette thèse, une approche de calcul de couplage multi-échelle et multi-physique en 2D et en 3D est présentée. La modélisation multi-échelle d’une structure consiste de l’échelle macro qui représente la réponse homogénéisée de la structure entière, tandis que l’échelle micro peut capturer les détails du comportement à la petite échelle du matériau, où des mécanismes inélastiques, tels que la plasticité ou l’endommagement, peuvent être pris en compte. L’intérieur de chaque macro-élément est rempli par le maillage à l’échelle micro qui s’y adapte entièrement. Les deux échelles sont couplées à travers le champ de déplacements imposé à l’interface. Le calcul par éléments finis est effectué, en utilisant une procédure de solution operator-split sur les deux échelles. En 2D, une discontinuité dans le champ de déplacements est introduite à l’échelle macro dans un élément fini Q4, pour pouvoir capturer l’adoucissement comportement d’un matériau piézoélectrique. Un degré de liberté supplémentaire qui représente le voltage est ajouté aux noeuds des macro-éléments de tétraèdre et d’hexaèdre en 3D. La poutre de Timoshenko comportant un modèle de commutation de polarisation est utilisée à l’échelle micro. Également, une formulation multi-échelle de Hellinger-Reissner a été développée et implémentée pour un simple patch test en électrostatique. La procédure proposée est mise en œuvre dans le logiciel de calcul par éléments finis FEAP - Finite Element Analysis Program. Pour simuler le comportement aux deux échelles, FEAP est modifié, et deux versions différentes du code sont obtenues - macroFEAP et microFEAP. Le couplage de ces codes est réalisé avec Component Template Library - CTL qui rend possible l’échange d’informations entre les deux échelles. Les capacités de cette approche multi-échelle en 2D et en 3D sont démontrées dans un environnement purement mécanique, mais aussi multi-physique. La formulation théorique et l’application algorithmique sont présentées, et les avantages de la méthode multi-échelle pour la modélisation des matériaux hétérogènes sont illustrés avec plusieurs exemples numériques
In this thesis, a multi-scale and multi-physics coupling computation procedure for a 2D and 3D setting is presented. When modeling the behavior of a structure by a multi-scale method, the macro-scale is used to describe the homogenized response of the structure, and the micro-scale to describe the details of the behavior on the smaller scale of the material where some inelastic mechanisms, like damage or plasticity, can be taken into account. The micro-scale mesh is defined for each macro-scale element in a way to fit entirely inside it. The two scales are coupled by imposing a constraint on the displacement field over their interface. The computation is performed using the operator split solution procedure on both scales, using the standard finite element method. In a 2D setting, an embedded discontinuity is implemented in the Q4 macroscale element to capture the softening behavior happening on the micro-scale. For the micro-scale element, a constant strain triangle (CST) is used. In a 3D setting, a macro-scale tetrahedral and hexahedral elements are developed, while on the micro-scale Timoshenko beam finite elements are used. This multi-scale methodology is extended with a multi-physics functionality, to simulate the behavior of a piezoelectric material. An additional degree of freedom (voltage) is added on the nodes of the 3D macro-scale tetrahedral and hexahedral elements. For the micro-scale element, a Timoshenko beam element with added polarization switching model is used. Also, a multi-scale Hellinger- Reissner formulation for electrostatics has been developed and implemented for a simple electrostatic patch test. For implementing the proposed procedure, Finite Element Analysis Program (FEAP) is used. To simulate the behavior on both macro and micro-scale, FEAP is modified and two different version of FEAP code are implemented – macroFEAP and microFEAP. For coupling, the two codes are exchanging information between them, and Component Template Library (CTL) is used. The capabilities of the proposed multi-scale approach in a 2D and 3D pure mechanics settings, but also multi-physics environment have been shown. The theoretical formulation and algorithmic implementation are described, and the advantages of the multi-scale approach for modeling heterogeneous materials are shown on several numerical examples
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Books on the topic "Cyber Algorithm"

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Analog - A Cyber-Dystopian Noir Vol. 1: Death by Algorithm. Image Comics, 2018.

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Sheng, Quan Z., and Brij B. Gupta. Machine Learning for Computer and Cyber Security: Principle, Algorithms, and Practices. Taylor & Francis Group, 2019.

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Sheng, Quan Z., and Brij B. Gupta. Machine Learning for Computer and Cyber Security: Principle, Algorithms, and Practices. Taylor & Francis Group, 2019.

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Sheng, Quan Z., and Brij B. Gupta. Machine Learning for Computer and Cyber Security: Principle, Algorithms, and Practices. Taylor & Francis Group, 2019.

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Sheng, Quan Z., and Brij B. Gupta. Machine Learning for Computer and Cyber Security: Principle, Algorithms, and Practices. Taylor & Francis Group, 2019.

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Book chapters on the topic "Cyber Algorithm"

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Hong, Sung-Soo, and Sang-Kil Kim. "Mobile Animation Algorithm for Cyber Museum." In Lecture Notes in Computer Science, 586–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44864-0_61.

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Nguyen, Viet T., Alla G. Kravets, and Tu Q. H. Duong. "Predicting Research Trend Based on Bibliometric Analysis and Paper Ranking Algorithm." In Cyber-Physical Systems, 109–23. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67892-0_10.

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Polyakov, Vladimir, Dmitriy Buhanov, Maxim Panchenko, Margarita Redkina, and Sergey Chernikov. "Research of the ELA Algorithm for Identifying Editing Fact in Jpeg Images." In Cyber-Physical Systems, 249–58. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67892-0_21.

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Chen, Yun, Yunlan Du, and Xiaomei Cao. "Density Peak Clustering Algorithm Based on Differential Privacy Preserving." In Science of Cyber Security, 20–32. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34637-9_2.

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Baruch, Moran, and Gil David. "Domain Generation Algorithm Detection Using Machine Learning Methods." In Cyber Security: Power and Technology, 133–61. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75307-2_9.

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Wang, Jing, Fuqi Song, Aihua Yin, and Hui Chen. "Firefly Algorithm Based on Dynamic Step Change Strategy." In Machine Learning for Cyber Security, 347–55. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62460-6_31.

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Cheng, Xianfu, Yanqing Yao, and Ao Liu. "An Improved Privacy-Preserving Stochastic Gradient Descent Algorithm." In Machine Learning for Cyber Security, 340–54. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62223-7_29.

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Alsuwat, Emad, Hatim Alsuwat, Marco Valtorta, and Csilla Farkas. "Cyber Attacks Against the PC Learning Algorithm." In ECML PKDD 2018 Workshops, 159–76. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13453-2_13.

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Peng, Jiao, and Shu Gong. "Optimization of Collaborative Filtering Algorithm in Movie Recommendation System." In Machine Learning for Cyber Security, 11–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62463-7_2.

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Liu, Bo, Jianhou Gan, Jun Wang, and Bin Wen. "Product Consistency Joint Detection Algorithm Based on Deep Learning." In Machine Learning for Cyber Security, 297–311. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62463-7_28.

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Conference papers on the topic "Cyber Algorithm"

1

Fisher, Ashwin, Rusty Baldwin, James T. Graham, and Ronald Riley. "Block-level algorithm classification based on RF side-channel." In Cyber Sensing 2018, edited by Peter Chin and Igor V. Ternovskiy. SPIE, 2018. http://dx.doi.org/10.1117/12.2303847.

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Riley, Ronald A., James T. Graham, Ashwin Fisher, Rusty O. Baldwin, and Ryan M. Fuller. "Generalization of algorithm recognition in RF side channels between devices." In Cyber Sensing 2018, edited by Peter Chin and Igor V. Ternovskiy. SPIE, 2018. http://dx.doi.org/10.1117/12.2304468.

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Dong, Huailin, Mingyuan He, and Ming Qiu. "Optimized Gray-Scale Image Watermarking Algorithm Based on DWT-DCT-SVD and Chaotic Firefly Algorithm." In 2015 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2015. http://dx.doi.org/10.1109/cyberc.2015.15.

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Chang, Jian, Bin Li, Guowei Zhang, Zhida Liang, and Cong Wang. "The Control Algorithm of 7 DOF Manipulator Based on Hybrid Force and Position Algorithm." In 2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER). IEEE, 2017. http://dx.doi.org/10.1109/cyber.2017.8446183.

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Chen, Min, XueDong Gao, and HuiFei Li. "An efficient parallel FP-Growth algorithm." In 2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2009. http://dx.doi.org/10.1109/cyberc.2009.5342148.

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Sun, Zhixin, Yadang Chen, and Zhixin Sun. "An Algorithm Based on Directed Graph." In 2010 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2010. http://dx.doi.org/10.1109/cyberc.2010.63.

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O'Brien, Neil S., Steven J. Johnston, Elizabeth E. Hart, Kamal Djidjeli, and Simon J. Cox. "Exploiting Cloud Computing for Algorithm Development." In 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2011. http://dx.doi.org/10.1109/cyberc.2011.60.

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Chen, Liang, Zhang Tong, Wen Liu, and Chengmin Gao. "Non-interactive Exponential Homomorphic Encryption Algorithm." In 2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2012. http://dx.doi.org/10.1109/cyberc.2012.44.

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Jones, Keith J., and Yong Wang. "An Optimized Running Window Entropy Algorithm." In 2018 National Cyber Summit (NCS). IEEE, 2018. http://dx.doi.org/10.1109/ncs.2018.00016.

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Belaidi, Abderrahmane, and Hadjira Belaidi. "Optimization algorithm of manipulator robot performances." In 2014 IEEE 4th Annual International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). IEEE, 2014. http://dx.doi.org/10.1109/cyber.2014.6917459.

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