2,222 research outputs found

    TOWARD AUTOMATED THREAT MODELING BY ADVERSARY NETWORK INFRASTRUCTURE DISCOVERY

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    Threat modeling can help defenders ascertain potential attacker capabilities and resources, allowing better protection of critical networks and systems from sophisticated cyber-attacks. One aspect of the adversary profile that is of interest to defenders is the means to conduct a cyber-attack, including malware capabilities and network infrastructure. Even though most defenders collect data on cyber incidents, extracting knowledge about adversaries to build and improve the threat model can be time-consuming. This thesis applies machine learning methods to historical cyber incident data to enable automated threat modeling of adversary network infrastructure. Using network data of attacker command and control servers based on real-world cyber incidents, specific adversary datasets can be created and enriched using the capabilities of internet-scanning search engines. Mixing these datasets with data from benign or non-associated hosts with similar port-service mappings allows for building an interpretable machine learning model of attackers. Additionally, creating internet-scanning search engine queries based on machine learning model predictions allows for automating threat modeling of adversary infrastructure. Automated threat modeling of adversary network infrastructure allows searching for unknown or emerging threat actor network infrastructure on the Internet.Major, Ukrainian Ground ForcesApproved for public release. Distribution is unlimited

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Evaluating Architectural Safeguards for Uncertain AI Black-Box Components

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    Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability

    An investigation of entorhinal spatial representations in self-localisation behaviours

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    Spatial-modulated cells of the medial entorhinal cortex (MEC) and neighbouring cortices are thought to provide the neural substrate for self-localisation behaviours. These cells include grid cells of the MEC which are thought to compute path integration operations to update self-location estimates. In order to read this grid code, downstream cells are thought to reconstruct a positional estimate as a simple rate-coded representation of space. Here, I show the coding scheme of grid cell and putative readout cells recorded from mice performing a virtual reality (VR) linear location task which engaged mice in both beaconing and path integration behaviours. I found grid cells can encode two unique coding schemes on the linear track, namely a position code which reflects periodic grid fields anchored to salient features of the track and a distance code which reflects periodic grid fields without this anchoring. Grid cells were found to switch between these coding schemes within sessions. When grid cells were encoding position, mice performed better at trials that required path integration but not on trials that required beaconing. This result provides the first mechanistic evidence linking grid cell activity to path integration-dependent behaviour. Putative readout cells were found in the form of ramp cells which fire proportionally as a function of location in defined regions of the linear track. This ramping activity was found to be primarily explained by track position rather than other kinematic variables like speed and acceleration. These representations were found to be maintained across both trial types and outcomes indicating they likely result from recall of the track structure. Together, these results support the functional importance of grid and ramp cells for self-localisation behaviours. Future investigations will look into the coherence between these two neural populations, which may together form a complete neural system for coding and decoding self-location in the brain

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Soundscape in Urban Forests

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    This Special Issue of Forests explores the role of soundscapes in urban forested areas. It is comprised of 11 papers involving soundscape studies conducted in urban forests from Asia and Africa. This collection contains six research fields: (1) the ecological patterns and processes of forest soundscapes; (2) the boundary effects and perceptual topology; (3) natural soundscapes and human health; (4) the experience of multi-sensory interactions; (5) environmental behavior and cognitive disposition; and (6) soundscape resource management in forests

    Comparing the Performance of Initial Coin Offerings to Crowdfunded Equity Ventures

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    Uncertainty in markets increases the likelihood of market failure due to volatility and suboptimal functioning. While initial coin offerings (ICOs) and crowdfunded equity (CFE) offerings may improve functioning in growing markets, there is a lack of knowledge and understanding pertaining to the relative efficiency and behavior of ICO markets compared to CFE markets, potentially perpetuating and thwarting the various communities they are intended to serve. The purpose of this correlational study was to compare a group of ICOs with a group of CFE offerings to identify predictive factors of funding outcomes related to both capital offering types. Efficient market hypothesis was the study’s theoretical foundation, and analysis of variance was used to answer the research question, which examined whether capital offering type predicted the amount of funds raised while controlling for access to the offering companies’ secondary control factors: historical financial data, pro forma financial projections, detailed product descriptions, video of product demonstrations, company website, company history, company leadership, and company investors. Relying on a random sample of 115 campaigns (84 ICOs and 31 CFE) from websites ICOdrops.com, localstake.com, fundable.com, and mainvest.com, results showed differences in mean funds raised between CFEs and ICOs (346,075comparedto346,075 compared to 4,756,464, respectively). ANOVA results showed no single secondary control factors and only one two-factor interaction (company leadership and company investors) influenced mean funds raised. This study may contribute to positive social change by informing best practices among market participants including entrepreneurs, regulators, scholars, and investors

    MetaOmniCity: Towards urban metaverse cyberspaces using immersive smart city digital twins

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    The movie - The Matrix (1999) - boosted our imagination about how further we can be immersed within the cyber world, i.e., how further the cyber world can be indistinguishable from the real world with the metaverse space travel. Nobody had expected involving the creators that the aspirational fictional virtual worlds such as "ActiveWorlds (1995)", and ``Second Life (2003)'' with many urban experiences embedded into a rich featured 3D environment would impact the way of experiencing our real urban environments. Are we going to feel/become ourselves - our cyber-physical presence (e.g., our augmented avatars) - in other mirror worlds doing many other things? Are the created imaginary worlds becoming a part of the real worlds or vice versa? The recent once-in-a-lifetime pandemic has confirmed the importance of location and time-independent Digital Twins (DTs) (i.e., virtual scale models) of cities and their automated services that can provide everybody with equity and accessibility by democratising all types of services leading to increased Quality of Life (QoL). This study analyses how the metaverse (3D elevation of linear Internet), that aims to build high-fidelity virtual worlds with which to interact with the real world, can be engaged within the Smart City (SC) ecosystem with high immersive Quality of Experiences (QoE) and an urban metaverse ecosystem framework — MetaOmniCity — that is designed to demonstrate a variety of insights and orchestrational directions for policymakers, city planners and all other stakeholders about how to transform data-driven SCs with DTs into virtually inhabitable cities with a network of shared urban experiences from a metaverse point of view. MetaOmniCity, allowing the metaversification of cities with granular virtual societies, i.e., MetaSocieties, and eliminating the boundaries (e.g., time, space and language) between the real world and their virtual counterparts, can be shaped to the particular requirements and features of cities. This can pave the way for immersive globalisation with the bigger and richer metaverse of Country (MoC) and metaverse of World (MoW) being an immersive DT of the broader universe with digitally connected cities by removing physical borders. MetaOmniCity is expected to accelerate the building, deployment, and adoption of immersive urban metaverse worlds/networks for citizens to interface with as an extension of real urban social and individual experiences
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