Machine Learning Use Cases in Cybersecurity
The problem regarding the use of machine learning in cybersecurity is difficult to solve because the advances in the field offer many opportunities that it is challenging to find exceptional and beneficial use cases for implementation and decision making. Moreover, such technologies can be used by intruders to attack computer systems. The goal of this paper to explore machine learning usage in cybersecurity and cyberattack and provide a model of machine learning-powered attack.
The paper makes a brief introduction into multiple classifier systems and describes a particular algorithm which improves classification accuracy by making a recommendation of an algorithm to an object. This recommendation is done under a hypothesis that a classifier is likely to predict the label of the object correctly if it has correctly classified its neighbors. The process of assigning a classifier to each object involves here the apparatus of Formal Concept Analysis. We explain the principle of the algorithm on a toy example and describe experiments with real-world datasets.
The paper deals with the problems of creating and tuning a system of automated anaphora resolution for Russian. Such a system is introduced, combining rule-based and machine learning approaches. It shows F-measure from 0.51 to 0.59. Freeling serves as an underlying morphological layer and an account of its quality is given, with its influence on anaphora resolution workflow. The anaphora resolution system itself is available to download and use, coming with online demo.
The volume contains the abstracts of the 12th International Conference "Intelligent Data Processing: Theory and Applications". The conference is organized by the Russian Academy of Sciences, the Federal Research Center "Informatics and Control" of the Russian Academy of Sciences and the Scientific and Coordination Center "Digital Methods of Data Mining". The conference has being held biennially since 1989. It is one of the most recognizable scientific forums on data mining, machine learning, pattern recognition, image analysis, signal processing, and discrete analysis. The Organizing Committee of IDP-2018 is grateful to Forecsys Co. and CFRS Co. for providing assistance in the conference preparation and execution. The conference is funded by RFBR, grant 18-07-20075. The conference website http://mmro.ru/en/.
Data management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry. Numerous types of applications and services have been studied and re-examined in this field resulting in this edited volume which includes chapters on effective approaches for dealing with the inherent complexity within data management and analysis. This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas.
In an effort to make reading more accessible, an automated readability formula can help students to retrieve appropriate material for their language level. This study attempts to discover and analyze a set of possible features that can be used for single-sentence readability prediction in Russian. We test the influence of syntactic features on predictability of structural complexity. The readability of sentences from SynTagRus corpus was marked up manually and used for evaluation.
This paper is an overview of the current issues and tendencies in Computational linguistics. The overview is based on the materials of the conference on computational linguistics COLING’2012. The modern approaches to the traditional NLP domains such as pos-tagging, syntactic parsing, machine translation are discussed. The highlights of automated information extraction, such as fact extraction, opinion mining are also in focus. The main tendency of modern technologies in Computational linguistics is to accumulate the higher level of linguistic analysis (discourse analysis, cognitive modeling) in the models and to combine machine learning technologies with the algorithmic methods on the basis of deep expert linguistic knowledge.
We present a universal method for algorithmic trading in Stock Market which performs asymptotically at least as well as any stationary trading strategy that computes the investment at each step using continuous function of the side information. In the process of the game, a trader makes decisions using predictions computed by a randomized well-calibrated algorithm. We use Dawid's notion of calibration with more general checking rules and some modication of Kakade and Foster's randomized rounding algorithm for computing the well-calibrated forecasts. The method of randomized calibration is combined with Vovk's method of defensive forecasting in RKHS. Unlike in statistical theory, no stochastic assumptions are made about the stock prices.
Modern transport systems are characterized by the development and implementation of intelligent transport technologies. Today, dynamic forecast models are not used in practice in the operation of a passenger terminal. Decision making is based on some regulatory values for passenger traffic, but this is not sufficient for efficient terminal management. Modern passenger terminals are characterized by dynamic process variability and consideration of diverse options, taking into account the criteria of safety, reliability analysis, and the continuous research of passenger processing. For any modern marine passenger terminal, it is necessary to use the tool to simulate passenger flows in dynamics. Only in this way it is possible to obtain the analytical information and use it for decision making when solving the problem of the amount of personnel required for passenger service, transport safety, some forecasting tasks and so on. Of particular relevance is the choice of the mathematical transport model and the practical conditions for the implementation of the model in the real terminal operation. In this article, the analysis technique of intelligent simulation-based terminal services provides a new mathematical model of passenger movement inside the terminal and presents a new software instrument. Moreover, the conditions of implementation of some transportation models during the operation of marine passenger terminal are examined. The study represents an example of analytical information used for the forecast of the terminal operations, the analysis of the workload and the efficiency of the organization of the marine terminal.
This book constitutes the joint refereed proceedings of the 17th International Conference on Next Generation Wired/Wireless Advanced Networks and Systems, NEW2AN 2017, the 10th Conference on Internet of Things and Smart Spaces, ruSMART 2017. The 71 revised full papers presented were carefully reviewed and selected from 202 submissions. The papers of NEW2AN focus on advanced wireless networking and applications; lower-layer communication enablers; novel and innovative approaches to performance and efficiency analysis of ad-hoc and machine-type systems; employed game-theoretical formulations, Markov chain models, and advanced queuing theory; grapheme and other emerging material, photonics and optics; generation and processing of signals; and business aspects. The ruSMART papers deal with fully-customized applications and services. The NsCC Workshop papers capture the current state-of-the-art in the field of molecular and nanoscale communications such as information, communication and network theoretical analysis of molecular and nanonetwork, mobility in molecular and nanonetworks; novel and practical communication protocols; routing schemes and architectures; design/engineering/evaluation of molecular and nonoscale communication systems; potential applications and interconnections to the Internet (e.g. the Internet of Nano Things).
The conference “2021 Systems of signals generating and processing in the field of on board communications” is organized with technical sponsorship of Russian (Moscow) IEEE Circuits and Systems (CAS04) Chapter IEEE Region 8, Russian Section Chapter, MTT/ED and Institute of Radio and Information Systems Association (IRIS), Vienna, Austria. The conference featured invited researchers, educators, managers, and graduate students, whose research activity, case studies or best practices, are shedding light on the theory or practice of engineering, include modern digital transportation systems design and technical operation, radio waves propagation, transmitting, receiving and processing signals in television and radio broadcasting devices, information technologies in transport. The main areas of the conference “Systems of signals generating and processing in the field of on board communications” include modern digital transportation systems design and technical operation, radio waves propagation, transmitting, receiving and processing signals in television and radio broadcasting devices, information technologies in transport. FIELD OF INTEREST: Components, Circuits, Devices and Systems; General Topics for Engineers; Signal Processing and Analysis. Reports presented at the conference are grouped in 6 sections: 1. Antennas and Radio Waves Propagation. 2. Navigation and Mathematical Algorithms of an Object Space Orientation. 3. Radiofrequency Applications. 4. Wire and Optical Communication and Control Systems. 5. Intelligent Transport Systems (ITS): Sub-section 1: Use of digital ITS infrastructure in telematic control systems on urban passenger transport Sub-section 2: Peculiarities of data exchange in cooperative ITS Sub-section 3: Theoretical Aspects of Artificial Intelligence Systems Development for Transportation Engineering Sub-section 4: Test methods of motor vehicles integrated into an intelligent transport environment 6. Digital signal processing in on-board radio systems
Описывается созданный макет манипулятора с биоэлектрическим управлением. Манипулятор сделан в форме человеческой ладони, движение пальцев которой управляется через электромиосигналы оператора. В среде LabVIEW разработан виртуальный прибор, позволяющий с помощью дискретного вейвлет-преобразования осуществить анализ электромиосигналов оператора, определить моменты мышечной активности и сформировать по результатам анализа сигналы управления манипулятором.
Let G be a semisimple algebraic group whose decomposition into the product of simple components does not contain simple groups of type A, and P⊆G be a parabolic subgroup. Extending the results of Popov , we enumerate all triples (G, P, n) such that (a) there exists an open G-orbit on the multiple flag variety G/P × G/P × . . . × G/P (n factors), (b) the number of G-orbits on the multiple flag variety is finite.
I give the explicit formula for the (set-theoretical) system of Resultants of m+1 homogeneous polynomials in n+1 variables