Sculpting reality from our dreams: Prefigurative design for civic engagement

At their core, organizing and activist work are about envisioning and working towards an alternative, more just political future. Various digital tools are used to support activist work, however these tools engage with values that are at odds with activist practices: where many activists do work in the service of social justice and equity, the digital tools they use are often corporate made, and thus support the status quo, i.e. profit generation, cis-heteropatriarchy, white supremacy, oppression. The ideals underlying activists’ equitable visions—of a more accessible and just future—drive their practices. This intentional alignment falls under the purview of prefigurative politics, where political work “express[es] the political ‘ends’ of their actions through their ‘means.’” [53] If activists envision a more democratic future, they adopt more equitable practices in the present in anticipation of building a more equitable future. This dissertation explores the role of digital tools to contribute to—to prefigure—alternative, more radical political values. My work uses design research and anarchist literature to explore the opportunities that ICTs offer in support of radically progressive political organizing. This work offers prefigurative design as an approach for designers and practitioners who work with communities in service of progressive political change. Prefigurative design is an orientation within HCI design and research that encourages critical reflection of research and design practices to better align design artifacts and processes with anarchist goals of anti-oppression and collective liberation, ultimately building counter-structures to replace existing institutions complicit in violence and oppression.Ph.D

Internet Health Report 2019

This annual report is a call to action to recognize the things that are having an impact on the internet today, and to embrace the notion that we as humans can change how we make money, govern societies, and interact with one another online. We invite you to participate in setting an agenda for how we can work together to create an internet that truly puts people first. This book is neither a country-level index nor a doomsday clock. Our intention is to show that while the worldwide consequences of getting things wrong with the internet could be huge - for peace and security, for political and individual freedoms, for human equality - the problems are never so great that nothing can be done. More people than you imagine are working to make the internet healthier by applying their skills, creativity, and personal bravery to business, technology, activism, policy and regulation, education, and community development

Data Privacy and Trust in Cloud Computing

This open access book brings together perspectives from multiple disciplines including psychology, law, IS, and computer science on data privacy and trust in the cloud. Cloud technology has fueled rapid, dramatic technological change, enabling a level of connectivity that has never been seen before in human history. However, this brave new world comes with problems. Several high-profile cases over the last few years have demonstrated cloud computing's uneasy relationship with data security and trust. This volume explores the numerous technological, process and regulatory solutions presented in academic literature as mechanisms for building trust in the cloud, including GDPR in Europe. The massive acceleration of digital adoption resulting from the COVID-19 pandemic is introducing new and significant security and privacy threats and concerns. Against this backdrop, this book provides a timely reference and organising framework for considering how we will assure privacy and build trust in such a hyper-connected digitally dependent world. This book presents a framework for assurance and accountability in the cloud and reviews the literature on trust, data privacy and protection, and ethics in cloud computing

INTRUSION PREDICTION SYSTEM FOR CLOUD COMPUTING AND NETWORK BASED SYSTEMS

Cloud computing offers cost effective computational and storage services with on-demand scalable capacities according to the customers’ needs. These properties encourage organisations and individuals to migrate from classical computing to cloud computing from different disciplines. Although cloud computing is a trendy technology that opens the horizons for many businesses, it is a new paradigm that exploits already existing computing technologies in new framework rather than being a novel technology. This means that cloud computing inherited classical computing problems that are still challenging. Cloud computing security is considered one of the major problems, which require strong security systems to protect the system, and the valuable data stored and processed in it. Intrusion detection systems are one of the important security components and defence layer that detect cyber-attacks and malicious activities in cloud and non-cloud environments. However, there are some limitations such as attacks were detected at the time that the damage of the attack was already done. In recent years, cyber-attacks have increased rapidly in volume and diversity. In 2013, for example, over 552 million customers’ identities and crucial information were revealed through data breaches worldwide [3]. These growing threats are further demonstrated in the 50,000 daily attacks on the London Stock Exchange [4]. It has been predicted that the economic impact of cyber-attacks will cost the global economy $3 trillion on aggregate by 2020 [5]. This thesis focused on proposing an Intrusion Prediction System that is capable of sensing an attack before it happens in cloud or non-cloud environments. The proposed solution is based on assessing the host system vulnerabilities and monitoring the network traffic for attacks preparations. It has three main modules. The monitoring module observes the network for any intrusion preparations. This thesis proposes a new dynamic-selective statistical algorithm for detecting scan activities, which is part of reconnaissance that represents an essential step in network attack preparation. The proposed method performs a statistical selective analysis for network traffic searching for an attack or intrusion indications. This is achieved by exploring and applying different statistical and probabilistic methods that deal with scan detection. The second module of the prediction system is vulnerabilities assessment that evaluates the weaknesses and faults of the system and measures the probability of the system to fall victim to cyber-attack. Finally, the third module is the prediction module that combines the output of the two modules and performs risk assessments of the system security from intrusions prediction. The results of the conducted experiments showed that the suggested system outperforms the analogous methods in regards to performance of network scan detection, which means accordingly a significant improvement to the security of the targeted system. The scanning detection algorithm has achieved high detection accuracy with 0% false negative and 50% false positive. In term of performance, the detection algorithm consumed only 23% of the data needed for analysis compared to the best performed rival detection method

State sovereignty and capitalism's relationship in the digital age. A critical analysis of platform capitalism, collaborative governance, and big data.

openThe aim of the research is to analyse the relationship between state sovereignty and market capitalism starting from the ‘80s in the western countries, after the advent of the new Information and Communication Technologies (ICTs). In order to do so, the thesis will display a schematic critique of the new forms of platform capitalism, platform urbanism, and big data analysis. The chapters will follow the three power relations between state, market, and citizens, assessing the various problems concerning the use of big data, such as security issues, exploitation, extraction of value, and democratic accountability. Apart from an organic critique, the following research’s main thesis is that the collaborative governance is a new conjunction ring between capitalism and state power, that brought into existence a new market of public service delivery and a sell-out of state political legitimacy. In the first chapter I will outline the historical framework that brought the diffusion of the ICTs, marking out the economical and political changes following the ‘80s. The second chapter will analyse the power relation between State and citizens. Following the two cases of Cambridge Analytica and Edward Snowden, I will discuss the evolution of state security and the riskiness related to big data for the democratic accountability. The third chapter will discuss the platform urbanism and the critiques concerning the Smart cities. With a critical perspective about collaborative governance, I will assert that in the last decades a new market based on the public service delivery has expanded, creating accountability and legitimacy issues for the western democracies. In the fourth and last chapter I will examine the power relation between citizens and the market, discussing the platform capitalism, the gig economy and the new forms of extraction of value related to the use of big data.The aim of the research is to analyse the relationship between state sovereignty and market capitalism starting from the ‘80s in the western countries, after the advent of the new Information and Communication Technologies (ICTs). In order to do so, the thesis will display a schematic critique of the new forms of platform capitalism, platform urbanism, and big data analysis. The chapters will follow the three power relations between state, market, and citizens, assessing the various problems concerning the use of big data, such as security issues, exploitation, extraction of value, and democratic accountability. Apart from an organic critique, the following research’s main thesis is that the collaborative governance is a new conjunction ring between capitalism and state power, that brought into existence a new market of public service delivery and a sell-out of state political legitimacy. In the first chapter I will outline the historical framework that brought the diffusion of the ICTs, marking out the economical and political changes following the ‘80s. The second chapter will analyse the power relation between State and citizens. Following the two cases of Cambridge Analytica and Edward Snowden, I will discuss the evolution of state security and the riskiness related to big data for the democratic accountability. The third chapter will discuss the platform urbanism and the critiques concerning the Smart cities. With a critical perspective about collaborative governance, I will assert that in the last decades a new market based on the public service delivery has expanded, creating accountability and legitimacy issues for the western democracies. In the fourth and last chapter I will examine the power relation between citizens and the market, discussing the platform capitalism, the gig economy and the new forms of extraction of value related to the use of big data

Algorithmic Governance from the Bottom Up

Artificial intelligence and machine learning are both a blessing and a curse for governance. In theory, algorithmic governance makes government more efficient, more accurate, and more fair. But the emergence of automation in governance also rests on public-private collaborations that expand both public and private power, aggravate transparency and accountability gaps, and create significant obstacles for those seeking algorithmic justice. In response, a nascent body of law proposes technocratic policy changes to foster algorithmic accountability, ethics, and transparency. This Article examines an alternative vision of algorithmic governance, one advanced primarily by social and labor movements instead of technocrats and firms. The use of algorithmic governance in increasingly high-stakes settings has generated an outpouring of activism, advocacy, and resistance. This mobilization draws on the same concerns that animate budding policy responses. But social and labor movements offer an alternative source of constraints on algorithmic governance: direct resistance from the bottom up. These movements confront head-on the entanglement of economic power, racial hierarchy, and government surveillance. Using three case studies, this Article explores how tech workers and social movements are resisting and mobilizing against technologies that expand surveillance and funnel wealth to the private sector. Each case study illustrates how the intermingling of state and private power has required movements to engage both within and outside firms to counteract the growing appeal of automation. Yet the dominant approaches to regulating the government’s uses of technology continue to afford a privileged role to private firms and elite institutions, sidelining movement demands. The fundamental challenge posed by these movements will be whether — and how — law and policy can accommodate demands for bottom-up control. This Article sketches a new vision for algorithmic accountability, with a more vibrant role for workers and for the public in determining how firms and government institutions work together

Algorithmic Governance from the Bottom Up

Artificial intelligence and machine learning are both a blessing and a curse for governance. In theory, algorithmic governance makes government more efficient, more accurate, and more fair. But the emergence of automation in governance also rests on public-private collaborations that expand both public and private power, aggravate transparency and accountability gaps, and create significant obstacles for those seeking algorithmic justice. In response, a nascent body of law proposes technocratic policy changes to foster algorithmic accountability, ethics, and transparency.This Article examines an alternative vision of algorithmic governance, one advanced primarily by social and labor movements instead of technocrats and firms. The use of algorithmic governance in increasingly high-stakes settings has generated an outpouring of activism, advocacy, and resistance. This mobilization draws on the same concerns that animate budding policy responses. But social and labor movements offer an alternative source of constraints on algorithmic governance: direct resistance from the bottom up. These movements confront head-on the entanglement of economic power, racial hierarchy, and government surveillance. Using three case studies, this Article explores how tech workers and social movements are resisting and mobilizing against technologies that expand surveillance and funnel wealth to the private sector. Each case study illustrates how the intermingling of state and private power has required movements to engage both within and outside firms to counteract the growing appeal of automation. Yet the dominant approaches to regulating the government’s uses of technology continue to afford a privileged role to private firms and elite institutions, sidelining movement demands. The fundamental challenge posed by these movements will be whether—and how—law and policy can accommodate demands for bottom-up control. This Article sketches a new vision for algorithmic accountability, with a more vibrant role for workers and for the public in determining how firms and government institutions work together

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

25 Years of Ed Tech

In this lively and approachable volume based on his popular blog series, Martin Weller demonstrates a rich history of innovation and effective implementation of ed tech across higher education. From Bulletin Board Systems to blockchain, Weller follows the trajectory of education by focusing each chapter on a technology, theory, or concept that has influenced each year since 1994. Calling for both caution and enthusiasm, Weller advocates for a critical and research-based approach to new technologies, particularly in light of disinformation, the impact of social media on politics, and data surveillance trends. A concise and necessary retrospective, this book will be valuable to educators, ed tech practitioners, and higher education administrators, as well as students