Key characteristics to create optimized blockchain consensus algorithms

Blockchain is a fairly new technology and still in its infancy. As a result, many research papers are creating optimized consensus algorithms. Therefore, a need for key characteristics to create optimized blockchain consensus algorithms has been identified. This research paper presents the results of a systematic literature on identifying the main blockchain consensus algorithms and their associated advantages and disadvantages. Papers from four different databases were retrieved and after exclusion criteria were applied, 44 papers were ultimately included in the review. Results indicated that the five main consensus algorithms were Proof-of-Work (PoW), Proof-of-Stake (PoS), Practical Byzantine Fault Tolerance (PBFT), and Delegated Proof-of-Stake. The results further indicated that efficiency was the main advantage of the PoS, PBFT, PoA and hybrid consensus algorithms. The main disadvantage was “energy wastage” and was attributed to the PoW algorithm. Security concerns were the main disadvantage of the PoS algorithm. These findings were used to present key characteristics that future researchers can have in mind when creating optimized blockchain consensus algorithms.https://www.springer.com/series/558hj2022Informatic

Blockchain-enabled cybersecurity provision for scalable heterogeneous network: A comprehensive survey

Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance, transportation, healthcare, education, and supply chain management. Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges. However, the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes. There is the biggest challenge of data integrity and scalability, including significant computing complexity and inapplicable latency on regional network diversity, operating system diversity, bandwidth diversity, node diversity, etc., for decision-making of data transactions across blockchain-based heterogeneous networks. Data security and privacy have also become the main concerns across the heterogeneous network to build smart IoT ecosystems. To address these issues, today’s researchers have explored the potential solutions of the capability of heterogeneous network devices to perform data transactions where the system stimulates their integration reliably and securely with blockchain. The key goal of this paper is to conduct a state-of-the-art and comprehensive survey on cybersecurity enhancement using blockchain in the heterogeneous network. This paper proposes a full-fledged taxonomy to identify the main obstacles, research gaps, future research directions, effective solutions, and most relevant blockchain-enabled cybersecurity systems. In addition, Blockchain based heterogeneous network framework with cybersecurity is proposed in this paper to meet the goal of maintaining optimal performance data transactions among organizations. Overall, this paper provides an in-depth description based on the critical analysis to overcome the existing work gaps for future research where it presents a potential cybersecurity design with key requirements of blockchain across a heterogeneous network

Hybrid Warfare

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. Hybrid Warfare refers to a military strategy that blends conventional warfare, so-called ‘irregular warfare’ and cyber-attacks with other influencing methods, such as fake news, diplomacy and foreign political intervention. As Hybrid Warfare becomes increasingly commonplace, there is an imminent need for research bringing attention to how these challenges can be addressed in order to develop a comprehensive approach towards Hybrid Threats and Hybrid Warfare. This volume supports the development of such an approach by bringing together practitioners and scholarly perspectives on the topic and by covering the threats themselves, as well as the tools and means to counter them, together with a number of real-world case studies. The book covers numerous aspects of current Hybrid Warfare discourses including a discussion of the perspectives of key western actors such as NATO, the US and the EU; an analysis of Russia and China’s Hybrid Warfare capabilities; and the growing threat of cyberwarfare. A range of global case studies – featuring specific examples from the Baltics, Taiwan, Ukraine, Iran and Catalonia – are drawn upon to demonstrate the employment of Hybrid Warfare tactics and how they have been countered in practice. Finally, the editors propose a new method through which to understand the dynamics of Hybrid Threats, Warfare and their countermeasures, termed the ‘Hybridity Blizzard Model’. With a focus on practitioner insight and practicable International Relations theory, this volume is an essential guide to identifying, analysing and countering Hybrid Threats and Warfare

Responsible AI and Analytics for an Ethical and Inclusive Digitized Society

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Hybrid Warfare

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. Hybrid Warfare refers to a military strategy that blends conventional warfare, so-called ‘irregular warfare’ and cyber-attacks with other influencing methods, such as fake news, diplomacy and foreign political intervention. As Hybrid Warfare becomes increasingly commonplace, there is an imminent need for research bringing attention to how these challenges can be addressed in order to develop a comprehensive approach towards Hybrid Threats and Hybrid Warfare. This volume supports the development of such an approach by bringing together practitioners and scholarly perspectives on the topic and by covering the threats themselves, as well as the tools and means to counter them, together with a number of real-world case studies. The book covers numerous aspects of current Hybrid Warfare discourses including a discussion of the perspectives of key western actors such as NATO, the US and the EU; an analysis of Russia and China’s Hybrid Warfare capabilities; and the growing threat of cyberwarfare. A range of global case studies – featuring specific examples from the Baltics, Taiwan, Ukraine, Iran and Catalonia – are drawn upon to demonstrate the employment of Hybrid Warfare tactics and how they have been countered in practice. Finally, the editors propose a new method through which to understand the dynamics of Hybrid Threats, Warfare and their countermeasures, termed the ‘Hybridity Blizzard Model’. With a focus on practitioner insight and practicable International Relations theory, this volume is an essential guide to identifying, analysing and countering Hybrid Threats and Warfare

Graph-based, systems approach for detecting violent extremist radicalization trajectories and other latent behaviors, A

2017 Summer.Includes bibliographical references.The number and lethality of violent extremist plots motivated by the Salafi-jihadist ideology have been growing for nearly the last decade in both the U.S and Western Europe. While detecting the radicalization of violent extremists is a key component in preventing future terrorist attacks, it remains a significant challenge to law enforcement due to the issues of both scale and dynamics. Recent terrorist attack successes highlight the real possibility of missed signals from, or continued radicalization by, individuals whom the authorities had formerly investigated and even interviewed. Additionally, beyond considering just the behavioral dynamics of a person of interest is the need for investigators to consider the behaviors and activities of social ties vis-à-vis the person of interest. We undertake a fundamentally systems approach in addressing these challenges by investigating the need and feasibility of a radicalization detection system, a risk assessment assistance technology for law enforcement and intelligence agencies. The proposed system first mines public data and government databases for individuals who exhibit risk indicators for extremist violence, and then enables law enforcement to monitor those individuals at the scope and scale that is lawful, and account for the dynamic indicative behaviors of the individuals and their associates rigorously and automatically. In this thesis, we first identify the operational deficiencies of current law enforcement and intelligence agency efforts, investigate the environmental conditions and stakeholders most salient to the development and operation of the proposed system, and address both programmatic and technical risks with several initial mitigating strategies. We codify this large effort into a radicalization detection system framework. The main thrust of this effort is the investigation of the technological opportunities for the identification of individuals matching a radicalization pattern of behaviors in the proposed radicalization detection system. We frame our technical approach as a unique dynamic graph pattern matching problem, and develop a technology called INSiGHT (Investigative Search for Graph Trajectories) to help identify individuals or small groups with conforming subgraphs to a radicalization query pattern, and follow the match trajectories over time. INSiGHT is aimed at assisting law enforcement and intelligence agencies in monitoring and screening for those individuals whose behaviors indicate a significant risk for violence, and allow for the better prioritization of limited investigative resources. We demonstrated the performance of INSiGHT on a variety of datasets, to include small synthetic radicalization-specific data sets, a real behavioral dataset of time-stamped radicalization indicators of recent U.S. violent extremists, and a large, real-world BlogCatalog dataset serving as a proxy for the type of intelligence or law enforcement data networks that could be utilized to track the radicalization of violent extremists. We also extended INSiGHT by developing a non-combinatorial neighbor matching technique to enable analysts to maintain visibility of potential collective threats and conspiracies and account for the role close social ties have in an individual's radicalization. This enhancement was validated on small, synthetic radicalization-specific datasets as well as the large BlogCatalog dataset with real social network connections and tagging behaviors for over 80K accounts. The results showed that our algorithm returned whole and partial subgraph matches that enabled analysts to gain and maintain visibility on neighbors' activities. Overall, INSiGHT led to consistent, informed, and reliable assessments about those who pose a significant risk for some latent behavior in a variety of settings. Based upon these results, we maintain that INSiGHT is a feasible and useful supporting technology with the potential to optimize law enforcement investigative efforts and ultimately enable the prevention of individuals from carrying out extremist violence. Although the prime motivation of this research is the detection of violent extremist radicalization, we found that INSiGHT is applicable in detecting latent behaviors in other domains such as on-line student assessment and consumer analytics. This utility was demonstrated through experiments with real data. For on-line student assessment, we tested INSiGHT on a MOOC dataset of students and time-stamped on-line course activities to predict those students who persisted in the course. For consumer analytics, we tested the performance on a real, large proprietary consumer activities dataset from a home improvement retailer. Lastly, motivated by the desire to validate INSiGHT as a screening technology when ground truth is known, we developed a synthetic data generator of large population, time-stamped, individual-level consumer activities data consistent with an a priori project set designation (latent behavior). This contribution also sets the stage for future work in developing an analogous synthetic data generator for radicalization indicators to serve as a testbed for INSiGHT and other data mining algorithms

Unmanned Aircraft Systems in the Cyber Domain

Unmanned Aircraft Systems are an integral part of the US national critical infrastructure. The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. This textbook will fully immerse and engage the reader / student in the cyber-security considerations of this rapidly emerging technology that we know as unmanned aircraft systems (UAS). The first edition topics covered National Airspace (NAS) policy issues, information security (INFOSEC), UAS vulnerabilities in key systems (Sense and Avoid / SCADA), navigation and collision avoidance systems, stealth design, intelligence, surveillance and reconnaissance (ISR) platforms; weapons systems security; electronic warfare considerations; data-links, jamming, operational vulnerabilities and still-emerging political scenarios that affect US military / commercial decisions. This second edition discusses state-of-the-art technology issues facing US UAS designers. It focuses on counter unmanned aircraft systems (C-UAS) – especially research designed to mitigate and terminate threats by SWARMS. Topics include high-altitude platforms (HAPS) for wireless communications; C-UAS and large scale threats; acoustic countermeasures against SWARMS and building an Identify Friend or Foe (IFF) acoustic library; updates to the legal / regulatory landscape; UAS proliferation along the Chinese New Silk Road Sea / Land routes; and ethics in this new age of autonomous systems and artificial intelligence (AI).https://newprairiepress.org/ebooks/1027/thumbnail.jp

Stress resilience : meaning, measurement, and the effects of physical activity

In rodent models of human behaviour, physical activity builds stress resilience. In contrast, human studies physical activity and stress resilience have been limited, and when investigated, provided mixed results. These inconsistencies may be due to the ambiguous use of the term stress resilience in human studies, making it difficult to quantify. Therefore, I aimed to assess the effect of physical activity on stress resilience in humans, after first evaluating operational definitions of stress resilience. Initially, I evaluated the use of stress resilience across the literature to provide a definition that is consistent with the research base (Chapter 2). I subsequently defined stress resilience as an active process of adapting to unpredictable and uncontrollable stimuli. In Chapter 3, I systematically reviewed measures previously used to capture stress resilience in humans, including trait-based questionnaires, as well as affective and cardiorespiratory responses to stressful conditions. In Study 1 (Chapter 4) of this dissertation, I then assessed the convergent validity of these stress resilience measures , including the Brief Resilience Scale and the Connor-Davidson Resilience Scale, as well as various responses (i.e., affective balance, systolic blood pressure, rate pressure product, and multiple indices of heart rate variability) to three stressor conditions (i.e., no stress, auditory startles, and stressful video clips). Results of Study 1 indicated that no measure captured all elements of stress resilience, although some indices of heart rate variability were related to changes in affective balance and systolic blood pressure was related to the Brief Resilience Scale. Across two studies, I then evaluated the effect of physical activity on stress resilience using the measures from Study 1. Through a cross-sectional study (Study 2, Chapter 5), I found no difference between active participants (n = 16) and less active participants (n = 14) across stress resilience measures. Additionally, in Study 3 (Chapter 6), I found that an 8-week moderate physical activity intervention had no effect on these stress resilience measures in 14 participants from desk-based occupations. I did, however, find an increase in mood and reduction in systolic blood pressure post-intervention, compared to pre-intervention scores. I also discussed the feasibility of various recruitment techniques, intervention purity and adherence, as well as stress resilience measurement protocols for future intervention studies. Overall, this dissertation has provided a critical evaluation of the use and measurement of stress resilience, with findings indicating that physical activity may not enhance stress resilience in humans. I discuss differences in my findings, compared to rodent research, including the potential effects of environment enrichment and increased severity of measurement protocols in animal models. I also discuss limitations of stress resilience conceptualisation and provide suggestions for future research to navigate these challenges.Doctor of Philosoph

CLINICAL TRIALS AND DRUG REGULATION: A PHILOSOPHICAL INQUIRY

This thesis is organized around two overlapping questions: (1) whether and how the current approach to the regulation of new medicines should be modified to manage issues generated by new biomedical products, and (2) whether this issue may be reduced to an epistemological and methodological analyses. I explore and discuss some philosophical issues related to these questions