3,708 research outputs found

    Ciguatoxins

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    Ciguatoxins (CTXs), which are responsible for Ciguatera fish poisoning (CFP), are liposoluble toxins produced by microalgae of the genera Gambierdiscus and Fukuyoa. This book presents 18 scientific papers that offer new information and scientific evidence on: (i) CTX occurrence in aquatic environments, with an emphasis on edible aquatic organisms; (ii) analysis methods for the determination of CTXs; (iii) advances in research on CTX-producing organisms; (iv) environmental factors involved in the presence of CTXs; and (v) the assessment of public health risks related to the presence of CTXs, as well as risk management and mitigation strategies

    Expectations and expertise in artificial intelligence: specialist views and historical perspectives on conceptualisation, promise, and funding

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    Artificial intelligence’s (AI) distinctiveness as a technoscientific field that imitates the ability to think went through a resurgence of interest post-2010, attracting a flood of scientific and popular expectations as to its utopian or dystopian transformative consequences. This thesis offers observations about the formation and dynamics of expectations based on documentary material from the previous periods of perceived AI hype (1960-1975 and 1980-1990, including in-between periods of perceived dormancy), and 25 interviews with UK-based AI specialists, directly involved with its development, who commented on the issues during the crucial period of uncertainty (2017-2019) and intense negotiation through which AI gained momentum prior to its regulation and relatively stabilised new rounds of long-term investment (2020-2021). This examination applies and contributes to longitudinal studies in the sociology of expectations (SoE) and studies of experience and expertise (SEE) frameworks, proposing a historical sociology of expertise and expectations framework. The research questions, focusing on the interplay between hype mobilisation and governance, are: (1) What is the relationship between AI practical development and the broader expectational environment, in terms of funding and conceptualisation of AI? (2) To what extent does informal and non-developer assessment of expectations influence formal articulations of foresight? (3) What can historical examinations of AI’s conceptual and promissory settings tell about the current rebranding of AI? The following contributions are made: (1) I extend SEE by paying greater attention to the interplay between technoscientific experts and wider collective arenas of discourse amongst non-specialists and showing how AI’s contemporary research cultures are overwhelmingly influenced by the hype environment but also contribute to it. This further highlights the interaction between competing rationales focusing on exploratory, curiosity-driven scientific research against exploitation-oriented strategies at formal and informal levels. (2) I suggest benefits of examining promissory environments in AI and related technoscientific fields longitudinally, treating contemporary expectations as historical products of sociotechnical trajectories through an authoritative historical reading of AI’s shifting conceptualisation and attached expectations as a response to availability of funding and broader national imaginaries. This comes with the benefit of better perceiving technological hype as migrating from social group to social group instead of fading through reductionist cycles of disillusionment; either by rebranding of technical operations, or by the investigation of a given field by non-technical practitioners. It also sensitises to critically examine broader social expectations as factors for shifts in perception about theoretical/basic science research transforming into applied technological fields. Finally, (3) I offer a model for understanding the significance of interplay between conceptualisations, promising, and motivations across groups within competing dynamics of collective and individual expectations and diverse sources of expertise

    Adaptive Cybersecurity Training Framework for Social Media Risks

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    Social media has become embedded in our everyday lives, personal activities, and the workplace. Thus, educating users on emerging cybersecurity challenges for social media has become imperative. In this project, a systematic literature review (SLR) was conducted and a mix of approach analyses to derive a framework that identifies the activities involved in adapting cybersecurity training for social media risks. I collected answers from 641 Kuwaiti employees in various sectors: education, healthcare, leadership and management, arts, entertainment, the police, and military, and interviewed 25 people who serve as policymakers, cybersecurity trainers, and those who have experienced cybersecurity training before. The study found that a one-fits-all training approach is highly ineffective, as people’s understanding and knowledge can vary greatly. Features such as gender, age, educational level, job roles, and the trainees’ training preferences and perceptions are essential considerations for developing a robust training system. Additionally, the study found that job role and age constitute the main factors associated with social media cybersecurity risks. The findings reveal that employees working in the business and financial sectors are the riskiest group, as far as cybersecurity is concerned. Female employees are more vulnerable to cyberattacks than male employees, and the youngest employees are the most risk prone, employees with less than two years of experience, and those who are 55 years old or more, need more cybersecurity training, due to their lack of awareness on the subject. This work has led to formulate a risk equation that can assist policymakers and training providers in defining countermeasures against risks and prioritize the training for those who need it the most. The framework and its process were validated through several strategies involving 38 case studies, surveys, and interviews. The novel contribution of this research is the proposal of the framework, which is a high-level, holistic framework that can support and promote organizations in mitigating social media risks

    Faculty Of Education UNHI

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    Faculty Of Education UNH

    IoT Botnet Detection Using an Economic Deep Learning Model

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    The rapid progress in technology innovation usage and distribution has increased in the last decade. The rapid growth of the Internet of Things (IoT) systems worldwide has increased network security challenges created by malicious third parties. Thus, reliable intrusion detection and network forensics systems that consider security concerns and IoT systems limitations are essential to protect such systems. IoT botnet attacks are one of the significant threats to enterprises and individuals. Thus, this paper proposed an economic deep learning-based model for detecting IoT botnet attacks along with different types of attacks. The proposed model achieved higher accuracy than the state-of-the-art detection models using a smaller implementation budget and accelerating the training and detecting processes.Comment: The paper under reviewing proces

    Typing a Terrorist Attack: Using Tools from the War on Terror to Fight the War on Ransomware

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    The United States faces a grave challenge in its fight against cyberattacks from abroad. Chief among the foreign cyber threats comes from a finite number of “ransomware-as-a-service” gangs, which are responsible for extorting billions of dollars from American citizens and companies annually. Prosecuting these cybercriminals has proven exceedingly difficult. Law enforcement often struggles to forensically trace ransomware attacks, which makes identifying and prosecuting the perpetrators challenging. Moreover, even when prosecutors can identify the perpetrators of these attacks, the ransomware gangs are headquartered in foreign adversarial nations that do not extradite criminals to the United States. Finally, ransomware gangs are governed by complex structures that push the limits of joint criminal enterprise liability. While these challenges are complex, they are not unprecedented. The United States has crafted successful legal solutions in response to similar challenges in its fight against the War on Terror. This Comment analyzes one of these legal solutions from the War on Terror, 8 U.S.C. § 1189, which establishes the Foreign Terrorist Organization list and assesses whether the State Department can and should designate foreign ransomware gangs as “Foreign Terrorist Organizations” (FTOs). This Comment argues that ransomware gangs qualify as “foreign organizations,” engage in “terrorist activities” as defined under the statute, and threaten the national security of the United States. Thus, ransomware gangs meet the statutory requirements for designation as FTOs. Given the prosecutorial and investigatory benefits and the useful financial and political implications of the designation, this Comment argues that the State Department should list ransomware gangs as FTOs

    Reasoning in criminal intelligence analysis through an argumentation theory-based framework

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    This thesis provides an in-depth analysis of criminal intelligence analysts’ analytical reasoning process and offers an argumentation theory-based framework as a means to support that reasoning process in software applications. Researchers have extensively researched specific areas of criminal intelligence analysts’ sensemaking and reasoning processes over the decades. However, the research is fractured across different research studies and those research studies often have high-level descriptions of how criminal intelligence analysts formulate their rationale (argument). This thesis addresses this gap by offering low level descriptions on how the reasoning-formulation process takes place. It is presented as a single framework, with supporting templates, to inform the software implementation process. Knowledge from nine experienced criminal intelligence analysts from West Midlands Police and Belgium’s Local and Federal Police forces were elicited through a semi-structured interview for study 1 and the Critical Decision Method (CDM), as part of the Cognitive Task Analysis (CTA) approach, was used for study 2 and study 3. The data analysis for study 1 made use of the Qualitative Conventional Content Analysis approach. The data analysis for study 2 made use of a mixed method approach, consisting out of Qualitative Directed Content Analysis and the Emerging Theme Approach. The data analysis for study 3 made use of the Qualitative Directed Content Analysis approach. The results from the three studies along with the concepts from the existing literature informed the construction of the argumentation theory-based framework. The evaluation study for the framework’s components made use of Paper Prototype Testing as a participatory design method over an electronic medium. The low-fidelity prototype was constructed by turning the frameworks’ components into software widgets that resembled widgets on a software application’s toolbar. Eight experienced criminal intelligence analysts from West Midlands Police and Belgium’s Local and Federal Police forces took part in the evaluation study. Participants had to construct their rationale using the available components as part of a simulated robbery crime scenario, which used real anonymised crime data from West Midlands Police force. The evaluation study made use of a Likert scale questionnaire to capture the participant’s views on how the frameworks’ components aided participants with; understanding what was going on in the analysis, lines-of-enquiry and; the changes in their level of confidence pertaining to their rationale. A non-parametric, one sample z-test was used for reporting the statistical results. The significance is at 5% (α=0.05) against a median of 3 for the z-test, where ÎŒ =3 represents neutral. The participants reported a positive experience with the framework’s components and results show that the framework’s components aided them with formulating their rationale and understanding how confident they were during different phases of constructing their rationale

    Redes sociais como fonte de dados alternativa no monitoramento de ĂĄguas-vivas

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    Orientador: Dr. MaurĂ­cio Almeida NoernbergCoorientadores: Dra. Carmem Satie Hara, Dr. Miodeli Nogueira JĂșniorTese (doutorado) - Universidade Federal do ParanĂĄ, Campus Pontal do ParanĂĄ - Centro de Estudos do Mar, Programa de PĂłs-Graduação em Sistemas Costeiros e OceĂąnicos. Defesa : Pontal do ParanĂĄ, 07/04/2023Inclui referĂȘnciasResumo: Na presente tese, foi investigada a utilidade das redes sociais em fornecer registros de observação de ĂĄguas-vivas ainda pouco estudadas no Brasil. Inicialmente, Ă© apresentada uma revisĂŁo sobre o uso da metodologia de ciĂȘncia cidadĂŁ passiva para extrair observaçÔes de espĂ©cies marinhas usando redes sociais. AlĂ©m disso, foram desenvolvidas metodologias sistematizadas para extrair e examinar postagens nas redes sociais para obter registros de ocorrĂȘncias de ĂĄguas-vivas. Com estas metodologias, foi obtido o primeiro registro da Stygiomedusa gigantea, bem como, o primeiro registro da mariafarinha (Ocypode quadrata) predando a caravela portuguesa (Physalia physalis) no Brasil. A partir dos dados das redes sociais, tambĂ©m foi possĂ­vel obter novas observaçÔes da Drymonema gorgo e da Physalia physalis na costa brasileira. Comparativamente Ă s outras fontes de dados, como literatura e ciĂȘncia cidadĂŁ, as observaçÔes das redes sociais corresponderam a cerca de 85% dos dados obtidos para D. gorgo e 60% para P. physalis. As pesquisas com redes sociais oferecem uma nova fonte de dados complementares sobre a biodiversidade marinha, sobretudo para as espĂ©cies de grande tamanho, como as espĂ©cies de ĂĄguas-vivas investigadas no presente estudo. Apesar da exploração das redes sociais como fonte de dados alternativa envolver desafios, com limitaçÔes nos dados, esta pesquisa mostra o potencial desta abordagem metodolĂłgica em contribuir para a gestĂŁo dos impactos negativos causados pelas ĂĄguas-vivas, bem como seus serviços ecossistĂȘmicos.Abstract: In the present thesis, it was investigated the usefulness of social networks in providing observation records of jellyfish which are still little studied in Brazil. Initially, it is presented a review of the use of passive citizen science methodology to extract observations of marine species using social media. In addition, it was developed systematized methodologies to extract and examine posts on social media to obtain records of jellyfish occurrences. These methodologies provided the first record of Stygiomedusa gigantea, as well as the first record of the ghost crab (Ocypode quadrata) preying on the Portuguese man-of-war (Physalia physalis) in Brazil. Using data from social media, it was also possible to obtain new observations of Drymonema gorgo and Physalia physalis on the Brazilian coast. Compared to other data sources, such as literature and citizen science, observations from social media accounted for about 85% of the data obtained for D. gorgo and 60% for P. physalis. Surveys with social media offer a new source of complementary data on marine biodiversity, especially on large species such as the jellyfish investigated in the present study. Although exploring social media as an alternative data source involves challenges, with data limitations, this research shows the potential of this methodological approach in contributing to the management of negative effects caused by jellyfish, as well as their ecosystem services

    Mitigating Emergent Safety and Security Incidents of CPS by a Protective Shell

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    In today's modern world, Cyber-Physical Systems (CPS) have gained widespread prevalence, offering tremendous benefits while also increasing society's dependence on them. Given the direct interaction of CPS with the physical environment, their malfunction or compromise can pose significant risks to human life, property, and the environment. However, as the complexity of CPS rises due to heightened expectations and expanded functional requirements, ensuring their trustworthy operation solely during the development process becomes increasingly challenging. This thesis introduces and delves into the novel concept of the 'Protective Shell' – a real-time safeguard actively monitoring CPS during their operational phases. The protective shell serves as a last line of defence, designed to detect abnormal behaviour, conduct thorough analyses, and initiate countermeasures promptly, thereby mitigating unforeseen risks in real-time. The primary objective of this research is to enhance the overall safety and security of CPS by refining, partly implementing, and evaluating the innovative protective shell concept. To provide context for collaborative systems working towards higher objectives — common within CPS as system-of-systems (SoS) — the thesis introduces the 'Emergence Matrix'. This matrix categorises outcomes of such collaboration into four quadrants based on their anticipated nature and desirability. Particularly concerning are outcomes that are both unexpected and undesirable, which frequently serve as the root cause of safety accidents and security incidents in CPS scenarios. The protective shell plays a critical role in mitigating these unfavourable outcomes, as conventional vulnerability elimination procedures during the CPS design phase prove insufficient due to their inability to proactively anticipate and address these unforeseen situations. Employing the design science research methodology, the thesis is structured around its iterative cycles and the research questions imposed, offering a systematic exploration of the topic. A detailed analysis of various safety accidents and security incidents involving CPS was conducted to retrieve vulnerabilities that led to dangerous outcomes. By developing specific protective shells for each affected CPS and assessing their effectiveness during these hazardous scenarios, a generic core for the protective shell concept could be retrieved, indicating general characteristics and its overall applicability. Furthermore, the research presents a generic protective shell architecture, integrating advanced anomaly detection techniques rooted in explainable artificial intelligence (XAI) and human machine teaming. While the implementation of protective shells demonstrate substantial positive impacts in ensuring CPS safety and security, the thesis also articulates potential risks associated with their deployment that require careful consideration. In conclusion, this thesis makes a significant contribution towards the safer and more secure integration of complex CPS into daily routines, critical infrastructures and other sectors by leveraging the capabilities of the generic protective shell framework.:1 Introduction 1.1 Background and Context 1.2 Research Problem 1.3 Purpose and Objectives 1.3.1 Thesis Vision 1.3.2 Thesis Mission 1.4 Thesis Outline and Structure 2 Design Science Research Methodology 2.1 Relevance-, Rigor- and Design Cycle 2.2 Research Questions 3 Cyber-Physical Systems 3.1 Explanation 3.2 Safety- and Security-Critical Aspects 3.3 Risk 3.3.1 Quantitative Risk Assessment 3.3.2 Qualitative Risk Assessment 3.3.3 Risk Reduction Mechanisms 3.3.4 Acceptable Residual Risk 3.4 Engineering Principles 3.4.1 Safety Principles 3.4.2 Security Principles 3.5 Cyber-Physical System of Systems (CPSoS) 3.5.1 Emergence 4 Protective Shell 4.1 Explanation 4.2 System Architecture 4.3 Run-Time Monitoring 4.4 Definition 4.5 Expectations / Goals 5 Specific Protective Shells 5.1 Boeing 737 Max MCAS 5.1.1 Introduction 5.1.2 Vulnerabilities within CPS 5.1.3 Specific Protective Shell Mitigation Mechanisms 5.1.4 Protective Shell Evaluation 5.2 Therac-25 5.2.1 Introduction 5.2.2 Vulnerabilities within CPS 5.2.3 Specific Protective Shell Mitigation Mechanisms 5.2.4 Protective Shell Evaluation 5.3 Stuxnet 5.3.1 Introduction 5.3.2 Exploited Vulnerabilities 5.3.3 Specific Protective Shell Mitigation Mechanisms 5.3.4 Protective Shell Evaluation 5.4 Toyota 'Unintended Acceleration' ETCS 5.4.1 Introduction 5.4.2 Vulnerabilities within CPS 5.4.3 Specific Protective Shell Mitigation Mechanisms 5.4.4 Protective Shell Evaluation 5.5 Jeep Cherokee Hack 5.5.1 Introduction 5.5.2 Vulnerabilities within CPS 5.5.3 Specific Protective Shell Mitigation Mechanisms 5.5.4 Protective Shell Evaluation 5.6 Ukrainian Power Grid Cyber-Attack 5.6.1 Introduction 5.6.2 Vulnerabilities in the critical Infrastructure 5.6.3 Specific Protective Shell Mitigation Mechanisms 5.6.4 Protective Shell Evaluation 5.7 Airbus A400M FADEC 5.7.1 Introduction 5.7.2 Vulnerabilities within CPS 5.7.3 Specific Protective Shell Mitigation Mechanisms 5.7.4 Protective Shell Evaluation 5.8 Similarities between Specific Protective Shells 5.8.1 Mitigation Mechanisms Categories 5.8.2 Explanation 5.8.3 Conclusion 6 AI 6.1 Explainable AI (XAI) for Anomaly Detection 6.1.1 Anomaly Detection 6.1.2 Explainable Artificial Intelligence 6.2 Intrinsic Explainable ML Models 6.2.1 Linear Regression 6.2.2 Decision Trees 6.2.3 K-Nearest Neighbours 6.3 Example Use Case - Predictive Maintenance 7 Generic Protective Shell 7.1 Architecture 7.1.1 MAPE-K 7.1.2 Human Machine Teaming 7.1.3 Protective Shell Plugin Catalogue 7.1.4 Architecture and Design Principles 7.1.5 Conclusion Architecture 7.2 Implementation Details 7.3 Evaluation 7.3.1 Additional Vulnerabilities introduced by the Protective Shell 7.3.2 Summary 8 Conclusion 8.1 Summary 8.2 Research Questions Evaluation 8.3 Contribution 8.4 Future Work 8.5 Recommendatio
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