124 research outputs found

    LIPIcs, Volume 274, ESA 2023, Complete Volume

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    LIPIcs, Volume 274, ESA 2023, Complete Volum

    Behavioral analysis in cybersecurity using machine learning: a study based on graph representation, class imbalance and temporal dissection

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    The main goal of this thesis is to improve behavioral cybersecurity analysis using machine learning, exploiting graph structures, temporal dissection, and addressing imbalance problems.This main objective is divided into four specific goals: OBJ1: To study the influence of the temporal resolution on highlighting micro-dynamics in the entity behavior classification problem. In real use cases, time-series information could be not enough for describing the entity behavior classification. For this reason, we plan to exploit graph structures for integrating both structured and unstructured data in a representation of entities and their relationships. In this way, it will be possible to appreciate not only the single temporal communication but the whole behavior of these entities. Nevertheless, entity behaviors evolve over time and therefore, a static graph may not be enoughto describe all these changes. For this reason, we propose to use a temporal dissection for creating temporal subgraphs and therefore, analyze the influence of the temporal resolution on the graph creation and the entity behaviors within. Furthermore, we propose to study how the temporal granularity should be used for highlighting network micro-dynamics and short-term behavioral changes which can be a hint of suspicious activities. OBJ2: To develop novel sampling methods that work with disconnected graphs for addressing imbalanced problems avoiding component topology changes. Graph imbalance problem is a very common and challenging task and traditional graph sampling techniques that work directly on these structures cannot be used without modifying the graph’s intrinsic information or introducing bias. Furthermore, existing techniques have shown to be limited when disconnected graphs are used. For this reason, novel resampling methods for balancing the number of nodes that can be directly applied over disconnected graphs, without altering component topologies, need to be introduced. In particular, we propose to take advantage of the existence of disconnected graphs to detect and replicate the most relevant graph components without changing their topology, while considering traditional data-level strategies for handling the entity behaviors within. OBJ3: To study the usefulness of the generative adversarial networks for addressing the class imbalance problem in cybersecurity applications. Although traditional data-level pre-processing techniques have shown to be effective for addressing class imbalance problems, they have also shown downside effects when highly variable datasets are used, as it happens in cybersecurity. For this reason, new techniques that can exploit the overall data distribution for learning highly variable behaviors should be investigated. In this sense, GANs have shown promising results in the image and video domain, however, their extension to tabular data is not trivial. For this reason, we propose to adapt GANs for working with cybersecurity data and exploit their ability in learning and reproducing the input distribution for addressing the class imbalance problem (as an oversampling technique). Furthermore, since it is not possible to find a unique GAN solution that works for every scenario, we propose to study several GAN architectures with several training configurations to detect which is the best option for a cybersecurity application. OBJ4: To analyze temporal data trends and performance drift for enhancing cyber threat analysis. Temporal dynamics and incoming new data can affect the quality of the predictions compromising the model reliability. This phenomenon makes models get outdated without noticing. In this sense, it is very important to be able to extract more insightful information from the application domain analyzing data trends, learning processes, and performance drifts over time. For this reason, we propose to develop a systematic approach for analyzing how the data quality and their amount affect the learning process. Moreover, in the contextof CTI, we propose to study the relations between temporal performance drifts and the input data distribution for detecting possible model limitations, enhancing cyber threat analysis.Programa de Doctorado en Ciencias y Tecnologías Industriales (RD 99/2011) Industria Zientzietako eta Teknologietako Doktoretza Programa (ED 99/2011

    Music and Digital Media

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    Anthropology has neglected the study of music. Music and Digital Media shows how and why this should be redressed. It does so by enabling music to expand the horizons of digital anthropology, demonstrating how the field can build interdisciplinary links to music and sound studies, digital/media studies, and science and technology studies. Music and Digital Media is the first comparative ethnographic study of the impact of digital media on music worldwide. It offers a radical and lucid new theoretical framework for understanding digital media through music, showing that music is today where the promises and problems of the digital assume clamouring audibility. The book contains ten chapters, eight of which present comprehensive original ethnographies; they are bookended by an authoritative introduction and a comparative postlude. Five chapters address popular, folk, art and crossover musics in the global South and North, including Kenya, Argentina, India, Canada and the UK. Three chapters bring the digital experimentally to the fore, presenting pioneering ethnographies of anextra-legal peer-to-peer site and the streaming platform Spotify, a series of prominent internet-mediated music genres, and the first ethnography of a global software package, the interactive music platform Max. The book is unique in bringing ethnographic research on popular, folk, art and crossover musics from the global North and South into a comparative framework on a large scale, and creates an innovative new paradigm for comparative anthropology. It shows how music enlarges anthropology while demanding to be understood with reference to classic themes of anthropological theory. Praise for Music and Digital Media ‘Music and Digital Media is a groundbreaking update to our understandings of sound, media, digitization, and music. Truly transdisciplinary and transnational in scope, it innovates methodologically through new models for collaboration, multi-sited ethnography, and comparative work. It also offers an important defense of—and advancement of—theories of mediation.’ Jonathan Sterne, Communication Studies and Art History, McGill University 'Music and Digital Media is a nuanced exploration of the burgeoning digital music scene across both the global North and the global South. Ethnographically rich and theoretically sophisticated, this collection will become the new standard for this field.' Anna Tsing, Anthropology, University of California at Santa Cruz 'The global drama of music's digitisation elicits extreme responses – from catastrophe to piratical opportunism – but between them lie more nuanced perspectives. This timely, absolutely necessary collection applies anthropological understanding to a deliriously immersive field, bringing welcome clarity to complex processes whose impact is felt far beyond what we call music.' David Toop, London College of Communication, musician and writer ‘Spanning continents and academic disciplines, the rich ethnographies contained in Music and Digital Media makes it obligatory reading for anyone wishing to understand the complex, contradictory, and momentous effects that digitization is having on musical cultures.’ Eric Drott, Music, University of Texas, Austin ‘This superb collection, with an authoritative overview as its introduction, represents the state of the art in studies of the digitalisation of music. It is also a testament to what anthropology at its reflexive best can offer the rest of the social sciences and humanities.’ David Hesmondhalgh, Media and Communication, University of Leeds ‘This exciting volume forges new ground in the study of local conditions, institutions, and sounds of digital music in the Global South and North. The book’s planetary scope and its commitment to the “messiness” of ethnographic sites and concepts amplifies emergent configurations and meanings of music, the digital, and the aesthetic.’ Marina Peterson, Anthropology, University of Texas, Austi

    Applied Methuerstic computing

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    For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

    Music and Digital Media: A planetary anthropology

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    Anthropology has neglected the study of music. Music and Digital Media shows how and why this should be redressed. It does so by enabling music to expand the horizons of digital anthropology, demonstrating how the field can build interdisciplinary links to music and sound studies, digital/media studies, and science and technology studies. Music and Digital Media is the first comparative ethnographic study of the impact of digital media on music worldwide. It offers a radical and lucid new theoretical framework for understanding digital media through music, showing that music is today where the promises and problems of the digital assume clamouring audibility. The book contains ten chapters, eight of which present comprehensive original ethnographies; they are bookended by an authoritative introduction and a comparative postlude. Five chapters address popular, folk, art and crossover musics in the global South and North, including Kenya, Argentina, India, Canada and the UK. Three chapters bring the digital experimentally to the fore, presenting pioneering ethnographies of an extra-legal peer-to-peer site and the streaming platform Spotify, a series of prominent internet-mediated music genres, and the first ethnography of a global software package, the interactive music platform Max. The book is unique in bringing ethnographic research on popular, folk, art and crossover musics from the global North and South into a comparative framework on a large scale, and creates an innovative new paradigm for comparative anthropology. It shows how music enlarges anthropology while demanding to be understood with reference to classic themes of anthropological theory

    Proceedings of the 19th Sound and Music Computing Conference

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    Proceedings of the 19th Sound and Music Computing Conference - June 5-12, 2022 - Saint-Étienne (France). https://smc22.grame.f
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