From online social network analysis to a user-centric private sharing system

Online social networks (OSNs) have become a massive repository of data constructed from individuals’ inputs: posts, photos, feedbacks, locations, etc. By analyzing such data, meaningful knowledge is generated that can affect individuals’ beliefs, desires, happiness and choices—a data circulation started from individuals and ended in individuals! The OSN owners, as the one authority having full control over the stored data, make the data available for research, advertisement and other purposes. However, the individuals are missed in this circle while they generate the data and shape the OSN structure. In this thesis, we started by introducing approximation algorithms for finding the most influential individuals in a social graph and modeling the spread of information. To do so, we considered the communities of individuals that are shaped in a social graph. The social graph is extracted from the data stored and controlled centrally, which can cause privacy breaches and lead to individuals’ concerns. Therefore, we introduced UPSS: the user-centric private sharing system, in which the individuals are considered as the real data owners and provides secure and private data sharing on untrusted servers. The UPSS’s public API allows the application developers to implement applications as diverse as OSNs, document redaction systems with integrity properties, censorship-resistant systems, health care auditing systems, distributed version control systems with flexible access controls and a filesystem in userspace. Accessing users’ data is possible only with explicit user consent. We implemented the two later cases to show the applicability of UPSS. Supporting different storage models by UPSS enables us to have a local, remote and global filesystem in userspace with one unique core filesystem implementation and having it mounted with different block stores. By designing and implementing UPSS, we show that security and privacy can be addressed at the same time in the systems that need selective, secure and collaborative information sharing without requiring complete trust

Accumunet: moderazione di un mercato/sistema CDN basato su peer-to-peer

Oggetto di questa tesi è lo studio delle problematiche connesse alla realizzazione di un meccanismo di moderazione e garanzia di qualità dei contenuti prodotti da una comunità priva di un sistema centralizzato di controll

Integrating Blockchain and Fog Computing Technologies for Efficient Privacy-preserving Systems

This PhD dissertation concludes a three-year long research journey on the integration of Fog Computing and Blockchain technologies. The main aim of such integration is to address the challenges of each of these technologies, by integrating it with the other. Blockchain technology (BC) is a distributed ledger technology in the form of a distributed transactional database, secured by cryptography, and governed by a consensus mechanism. It was initially proposed for decentralized cryptocurrency applications with practically proven high robustness. Fog Computing (FC) is a geographically distributed computing architecture, in which various heterogeneous devices at the edge of network are ubiquitously connected to collaboratively provide elastic computation services. FC provides enhanced services closer to end-users in terms of time, energy, and network load. The integration of FC with BC can result in more efficient services, in terms of latency and privacy, mostly required by Internet of Things systems

FinBook: literary content as digital commodity

This short essay explains the significance of the FinBook intervention, and invites the reader to participate. We have associated each chapter within this book with a financial robot (FinBot), and created a market whereby book content will be traded with financial securities. As human labour increasingly consists of unstable and uncertain work practices and as algorithms replace people on the virtual trading floors of the worlds markets, we see members of society taking advantage of FinBots to invest and make extra funds. Bots of all kinds are making financial decisions for us, searching online on our behalf to help us invest, to consume products and services. Our contribution to this compilation is to turn the collection of chapters in this book into a dynamic investment portfolio, and thereby play out what might happen to the process of buying and consuming literature in the not-so-distant future. By attaching identities (through QR codes) to each chapter, we create a market in which the chapter can ‘perform’. Our FinBots will trade based on features extracted from the authors’ words in this book: the political, ethical and cultural values embedded in the work, and the extent to which the FinBots share authors’ concerns; and the performance of chapters amongst those human and non-human actors that make up the market, and readership. In short, the FinBook model turns our work and the work of our co-authors into an investment portfolio, mediated by the market and the attention of readers. By creating a digital economy specifically around the content of online texts, our chapter and the FinBook platform aims to challenge the reader to consider how their personal values align them with individual articles, and how these become contested as they perform different value judgements about the financial performance of each chapter and the book as a whole. At the same time, by introducing ‘autonomous’ trading bots, we also explore the different ‘network’ affordances that differ between paper based books that’s scarcity is developed through analogue form, and digital forms of books whose uniqueness is reached through encryption. We thereby speak to wider questions about the conditions of an aggressive market in which algorithms subject cultural and intellectual items – books – to economic parameters, and the increasing ubiquity of data bots as actors in our social, political, economic and cultural lives. We understand that our marketization of literature may be an uncomfortable juxtaposition against the conventionally-imagined way a book is created, enjoyed and shared: it is intended to be

A Survey on Security and Privacy of 5G Technologies: Potential Solutions, Recent Advancements, and Future Directions

Security has become the primary concern in many telecommunications industries today as risks can have high consequences. Especially, as the core and enable technologies will be associated with 5G network, the confidential information will move at all layers in future wireless systems. Several incidents revealed that the hazard encountered by an infected wireless network, not only affects the security and privacy concerns, but also impedes the complex dynamics of the communications ecosystem. Consequently, the complexity and strength of security attacks have increased in the recent past making the detection or prevention of sabotage a global challenge. From the security and privacy perspectives, this paper presents a comprehensive detail on the core and enabling technologies, which are used to build the 5G security model; network softwarization security, PHY (Physical) layer security and 5G privacy concerns, among others. Additionally, the paper includes discussion on security monitoring and management of 5G networks. This paper also evaluates the related security measures and standards of core 5G technologies by resorting to different standardization bodies and provide a brief overview of 5G standardization security forces. Furthermore, the key projects of international significance, in line with the security concerns of 5G and beyond are also presented. Finally, a future directions and open challenges section has included to encourage future research.European CommissionNational Research Tomsk Polytechnic UniversityUpdate citation details during checkdate report - A