Foundations of Cryptoeconomic Systems

Blockchain networks and similar cryptoeconomic networks aresystems, specifically complex systems. They are adaptive networkswith multi-scale spatiotemporal dynamics. Individual actions towards a collective goal are incentivized with "purpose-driven" tokens. These tokens are equipped with cryptoeconomic mechanisms allowing a decentralized network to simultaneously maintain a universal state layer, support peer-to-peer settlement, andincentivize collective action. These networks therefore provide a mission-critical and safety-critical regulatory infrastructure for autonomous agents in untrusted economic networks. They also provide a rich, real-time data set reflecting all economic activities in their systems. Advances in data science and network sciencecan thus be leveraged to design and analyze these economic systems in a manner consistent with the best practices of modern systems engineering. Research that reflects all aspects of these socioeconomic networks needs (i) a complex systems approach, (ii) interdisciplinary research, and (iii) a combination of economic and engineering methods, here referred to as "economic systems engineering", for the regulation and control of these socio-economicsystems. This manuscript provides foundations for further research activities that build on these assumptions, including specific research questions and methodologies for future research in this field.Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc

Relational Differential Dynamic Logic

In the field of quality assurance of hybrid systems (that combine continuous physical dynamics and discrete digital control), Platzer's differential dynamic logic (dL) is widely recognized as a deductive verification method with solid mathematical foundations and sophisticated tool support. Motivated by benchmarks provided by our industry partner, we study a relational extension of dL, aiming to formally prove statements such as "an earlier deployment of the emergency brake decreases the collision speed." A main technical challenge here is to relate two states of two dynamics at different time points. Our main contribution is a theory of suitable simulations (a relational extension of differential invariants that are central proof methods in dL), and a derived technique of time stretching. The latter features particularly high applicability, since the user does not have to synthesize a simulation out of the air. We derive new inference rules for dL from these notions, and demonstrate their use over a couple of automotive case studies

Foundations of Cryptoeconomic Systems

Blockchain networks and similar cryptoeconomic networks are systems, specifically complex systems. They are adaptive networks with multiscale spatio-temporal dynamics. Individual actions may be incentivized towards a collective goal with “purpose-driven” tokens. Blockchain networks, for example, are equipped cryptoeconomic mechanisms that allow the decentralized network to simultaneously maintain a universal state layer, support peer-to-peer settlement, and incentivize collective action. These networks represent an institutional infrastructure upon which socioeconomic collaboration is facilitated – in the absence of intermediaries or traditional organizations. They provide a mission-critical and safety-critical regulatory infrastructure for autonomous agents in untrusted economic networks. Their tokens provide a rich, real-time data set reflecting all economic activities in their systems. Advances in network science and data science can thus be leveraged to design and analyze these economic systems in a manner consistent with the best practices of modern systems engineering. Research that reflects all aspects of these socioeconomic networks needs (i) a complex systems approach, (ii) interdisciplinary research, and (iii) a combination of economic and engineering methods, here referred to as “economic systems engineering,” for the regulation and control of these socioeconomic systems. This manuscript provides a conceptual framework synthesizing the research space and proceeds to outline specific research questions and methodologies for future research in this field, applying an inductive approach based on interdisciplinary literature review and relative contextualization of the works cited.Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc

Computable Analysis and Game Theory: From Foundations to Applications

This body of research showcases several facets of the intersection between computer science and game theory. On the foundational side, we explore the obstructions to the computability of Nash equilibria in the setting of computable analysis. In particular, we study the Weihrauch degree of the problem of finding a Nash equilibrium for a multiplayer game in normal form. We conclude that the Weihrauch degree Nash for multiplayer games lies between AoUC∗[0,1] and AoUC⋄[0,1] (Theorem 5.3). As a slight detour, we also explore the demarcation between computable and non-computable computational problems pertaining to the verification of machine learning. We demonstrate that many verification questions are computable without the need to specify a machine learning framework (Section 7.2). As well as looking into the theory of learners, robustness and sparisty of training data. On the application side, we study the use of Hypergames in Cybersecurity. We look into cybersecurity AND/OR attack graphs and how we could turn them into a hypergame (8.1). Hyper Nash equilibria is not an ideal solution for these games, however, we propose a regret-minimisation based solution concept. In Section 8.2, we survey the area of Hypergames and their connection to cybersecurity, showing that even if there is a small overlap, the reach is limited. We suggest new research directions such as adaptive games, generalisation and transferability (Section 8.3)

Smart Sensing: Selection, Prediction and Monitoring

A sensor is a device which is used to detect physical parameters of interest like temperature, pressure, or strain, performing the so called sensing process. This kind of device has been widely adopted in different fields such as aeronautics, automotive, security, logistics, health-care and more. The essential difference between a smart sensor and a standard sensor is its intelligence capability: smart sensors are able to capture and elaborate data from the environment while communicating and interacting with other systems in order to make predictions and find intelligent solutions based on the application needs. The first part of this thesis is focused on the problem of sensor selection in the context of virtual sensing of temperature in indoor environments, a topic of paramount importance which allows to increase the accuracy of the predictive models employed in the following phases by providing more informative data. In particular, virtual sensing refers to the process of estimating or predicting physical parameters without relying on physical sensors, using computational algorithms and predictive models to gather and analyze data for accurate predictions. We analyze the literature, propose and evaluate methodologies and solutions for sensor selection and placement based on machine learning techniques, including evolutionary algorithms. Thereafter, once determined which physical sensors to wield, the focus shifts to the actual methodology for virtual sensing strategies for the prediction of temperatures allowing to uniformly monitor uncovered or unreachable locations, reducing the sensors deployment costs and providing, at the same time, a fallback solution in case of sensor failures. For this purpose, we conduct a comprehensive assessment of different virtual sensing strategies including novel solutions proposed based on recurrent neural networks and graph neural networks able to effectively exploit spatio-temporal features. The methodologies considered so far are able to accurately complete the information coming from real physical sensors, allowing us to effectively carry out monitoring tasks such as anomaly or event detection. Therefore, the final part of this work looks at sensors from another, more formal, point of view. Specifically, it is devoted to the study and design of a framework aimed at pairing monitoring and machine learning techniques in order to detect, in a preemptive manner, critical behaviours of a system that could lead to a failure. This is done extracting interpretable properties, expressed in a given temporal logic formalism, from sensor data. The proposed framework is evaluated through an experimental assessment performed on benchmark datasets, and then compared to previous approaches from the literature

ROLE OF INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) IN HIV/AIDS HEALTH COMMUNICATION IN SLUMS (A Case of Kawangware Division, Nairobi Kenya)

Purpose: Information and Communication Technologies are key elements of a civil society response to the HIV/AIDS epidemic, enabling advocacy, mobilization, and empowerment of People Living with HIV (PLWHA), women, and other vulnerable groups. This study sought to investigate the role of Information and Communication Technology (ICT) in HIV/AIDS Health Communication in slums through a case study of a project sponsored by AfriAfya in Kawangware division, Nairobi Kenya. AfriAfya, also known as the African Network for Health Knowledge Management and Communication, is a consortium of health NGOs namely: Aga Khan Health Services; African Medical and Research Foundation (AMREF); CARE Kenya; Christian Health Association of Kenya; HealthNet Kenya; the Ministry of Health, Kenya; PLAN International; and World Vision International, Kenya. AfriAfya was set up in April 2000 to explore the ways of harnessing ICTs for community health in rural and marginalized communities.  The study was guided by the following specific objectives: (i) to analyze the ICT interventions and tools used in the fight against HIV/AIDS in Kenya; to examine the benefits derived from adoption of ICTs in the fight against HIV/AIDS in Kenyan slums; to assess the challenges faced in the adoption of ICTs in the fight against HIV/AIDS in the slums in Kenya; and to recommend strategies on how best to employ ICTs in the fight against HIV/AIDS in Kenyan slums. Methods: The data collected by this study was analyzed by descriptive statistics such as percentages, frequencies and tables. In addition, standard deviations and mean scores were used to present information pertaining to the study objectives. The information was presented and discussed as per the objectives and research questions of the study. Findings: Findings of the study indicate that all the four objectives were met as follows:- The tools used in the fight against HIV/AIDS in Kenya were established as being e-mail discussion groups, Internet, Dissemination of information on World Wide Web (www), Radio, Television, and  Distance learning systems. The interventions used in the fight against HIV/AIDS in Kenya were established as being Prevention:-Dissemination of prevention messages as well as prevention services to target groups such as commercial sex workers; School Based Education:- Education and life skills training in the schools for effecting appropriate behavioral changes among youth; and Education of Health Care Workers :- ICTs are being used to improve access to information, education, and communication for health workers using, Internet, email discussion groups, and distance learning systems. The benefits derived from adoption of ICTs in the fight against HIV/AIDS in Kenyan slums were determined as being Social change; empowerment and reduction of vulnerability; advocacy, mobilization, networking and capacity building; Remote consultations and diagnosis; Information sharing; Remote mentoring; Facilitation of Distance learning teaching; and Online Counseling. The challenges of adoption of the ICTs in HIV/AIDS Health Communication were established as being: - Limited connectivity; Poor ICT infrastructure status; High costs of accessing the Internet; and Language barrier. Key Words: Information & Communication Technology, HIV/AIDS, Community Based Organizations

Mobile, intelligent and autonomous policing tools and the law

This thesis resolves around problems arising for the existing legal framework from the use of novel software-­‐based policing tools during criminal investigations. The increasing dependence on information and communication technologies and the Internet means that more aspects of people’s lives move online, and crime follows them. This has triggered the development of innovative, autonomous investigative technologies that are increasingly replacing human officers for the policing of the online sphere. While only recently discussions of the legal status of embodied and unembodied robotical devices have gained more widespread attention, discussions of the legal status of autonomous agent technology are not new. They have focussed however in the past on applications in the private domain, enabling contract formation online. No systematic study has so far been carried out that looks at the use of autonomous agent technology when deployed by state actors, to fulfil core state functions. This thesis starts with the hypothesis that the use of automated, intelligent devices to replicate core police functions in the online world will increase in the future. Looking at first emerging technologies, but with an eye towards future deployment of much more capable software tools that fulfil policing functions on the Internet, this thesis looks at the challenges this poses for regulators and software developers. Based on extensive qualitative research interviews with stakeholders from two different jurisdictions (Germany & UK) this thesis finds that these novel policing technologies challenge existing legal frameworks, which are still premised on the parameters of the offline world. It therefore develops an alternative governance model for these policing tools, which enables their law-­‐compliant use and prevents rights violations of suspects. In doing so it draws upon both worlds, the technical and the legal, while also incorporating the empirical research results from the interviews with experts. The first part of this thesis analyses the technical foundations of these software-­‐based policing tools. Here, one of the key findings is that the current governance system focuses on ex-­‐ante authorisation of very specific, individual software tools without developing a systematic classification. This contradicts the principle of sustainable law making. To overcome this piecemeal approach, as a first contribution to existing research this work defines a new class of investigative technologies – mobile, intelligent and autonomous (MIA) policing tools ‐ based on the findings of the technical analysis. Identifying such a natural class of present and future technologies that pose the same type of legal issues should facilitate the sustainable governance of these new policing tools. The second part of this thesis analyses two specific legal issues: cross-­jurisdictional investigations and the evidentiary value of the seized data. These issues were identified as most pressing by the experts interviewed for this work. This analysis reveals that investigative activities of MIA tools are potentially in conflict with international law principles and criminal procedure law. In order to gain legitimacy, these new policing tools need to operate within the parameters of the existing legal framework. This thesis argues that given the unique technical capabilities of MIA tools, the primary approach to achieving this is to assign legal responsibility to these tools. The third part of this thesis develops a novel governance approach to ensure that MIA tools operate within the parameters of the legal framework, and therefore obtain legitimacy and relevance, also with regard to the investigative results. This approach builds on existing research identifying code as a regulatory modality and contributes to the field of legal theory. It constitutes a solution for the governance problems of MIA tools, however, it requires currently lacking collaboration among stakeholders and cross-­disciplinary research