992 research outputs found

    A Survey on Forensics and Compliance Auditing for Critical Infrastructure Protection

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    The broadening dependency and reliance that modern societies have on essential services provided by Critical Infrastructures is increasing the relevance of their trustworthiness. However, Critical Infrastructures are attractive targets for cyberattacks, due to the potential for considerable impact, not just at the economic level but also in terms of physical damage and even loss of human life. Complementing traditional security mechanisms, forensics and compliance audit processes play an important role in ensuring Critical Infrastructure trustworthiness. Compliance auditing contributes to checking if security measures are in place and compliant with standards and internal policies. Forensics assist the investigation of past security incidents. Since these two areas significantly overlap, in terms of data sources, tools and techniques, they can be merged into unified Forensics and Compliance Auditing (FCA) frameworks. In this paper, we survey the latest developments, methodologies, challenges, and solutions addressing forensics and compliance auditing in the scope of Critical Infrastructure Protection. This survey focuses on relevant contributions, capable of tackling the requirements imposed by massively distributed and complex Industrial Automation and Control Systems, in terms of handling large volumes of heterogeneous data (that can be noisy, ambiguous, and redundant) for analytic purposes, with adequate performance and reliability. The achieved results produced a taxonomy in the field of FCA whose key categories denote the relevant topics in the literature. Also, the collected knowledge resulted in the establishment of a reference FCA architecture, proposed as a generic template for a converged platform. These results are intended to guide future research on forensics and compliance auditing for Critical Infrastructure Protection.info:eu-repo/semantics/publishedVersio

    Climate Change and Critical Agrarian Studies

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    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Supporting Safety Analysis of Deep Neural Networks with Automated Debugging and Repair

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    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

    Artificial Intelligence and International Conflict in Cyberspace

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    This edited volume explores how artificial intelligence (AI) is transforming international conflict in cyberspace. Over the past three decades, cyberspace developed into a crucial frontier and issue of international conflict. However, scholarly work on the relationship between AI and conflict in cyberspace has been produced along somewhat rigid disciplinary boundaries and an even more rigid sociotechnical divide – wherein technical and social scholarship are seldomly brought into a conversation. This is the first volume to address these themes through a comprehensive and cross-disciplinary approach. With the intent of exploring the question ‘what is at stake with the use of automation in international conflict in cyberspace through AI?’, the chapters in the volume focus on three broad themes, namely: (1) technical and operational, (2) strategic and geopolitical and (3) normative and legal. These also constitute the three parts in which the chapters of this volume are organised, although these thematic sections should not be considered as an analytical or a disciplinary demarcation

    Digital agriculture: research, development and innovation in production chains.

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    Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil

    Comparing the Performance of Initial Coin Offerings to Crowdfunded Equity Ventures

    Get PDF
    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
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