Analysis and design of security mechanisms in the context of Advanced Persistent Threats against critical infrastructures

Industry 4.0 can be defined as the digitization of all components within the industry, by combining productive processes with leading information and communication technologies. Whereas this integration has several benefits, it has also facilitated the emergence of several attack vectors. These can be leveraged to perpetrate sophisticated attacks such as an Advanced Persistent Threat (APT), that ultimately disrupts and damages critical infrastructural operations with a severe impact. This doctoral thesis aims to study and design security mechanisms capable of detecting and tracing APTs to ensure the continuity of the production line. Although the basic tools to detect individual attack vectors of an APT have already been developed, it is important to integrate holistic defense solutions in existing critical infrastructures that are capable of addressing all potential threats. Additionally, it is necessary to prospectively analyze the requirements that these systems have to satisfy after the integration of novel services in the upcoming years. To fulfill these goals, we define a framework for the detection and traceability of APTs in Industry 4.0, which is aimed to fill the gap between classic security mechanisms and APTs. The premise is to retrieve data about the production chain at all levels to correlate events in a distributed way, enabling the traceability of an APT throughout its entire life cycle. Ultimately, these mechanisms make it possible to holistically detect and anticipate attacks in a timely and autonomous way, to deter the propagation and minimize their impact. As a means to validate this framework, we propose some correlation algorithms that implement it (such as the Opinion Dynamics solution) and carry out different experiments that compare the accuracy of response techniques that take advantage of these traceability features. Similarly, we conduct a study on the feasibility of these detection systems in various Industry 4.0 scenarios

The structure and dynamics of multilayer networks

In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of the network affects processes and dynamics.Comment: In Press, Accepted Manuscript, Physics Reports 201

Towards a theory of digital network de/centralization: platform-infrastructure lessons drawn from blockchain

Global digital platforms are conquering the world and rely critically on digital infrastructures to function, yet little research has explored the fundamental interrelationship between the two. This working paper argues that understanding centralization and decentralization in digital networks as asymmetry and symmetry in mutual interdependencies between the constitutive elements of a digital network can help us understand the platform-infrastructure relationship more fundamentally (and vice versa). To this end, the paper proposes, as a starting point, the in-depth analytical and literature study of blockchain networks as a particularly revealing type of digital platform/infrastructure duality. The paper proposes an analytical model for characterizing de/centralization in digital networks and maps this onto blockchain networks. Based on this, the paper explores the de/centralization of blockchain, arguing that the extant blockchain literature largely has failed in providing a comprehensive understanding of de/centralization by not considering the complex second-order interdependencies between the different constitutive dimensions of a blockchain: the symbolic, technological and political dimension. Based on this, the paper provides an analysis of the meaning of de/centralization in blockchain networks by studying the interdependencies between its constitutive elements of coin, network technology, and social community

Actor-Network VS Network Analysis VS Digital Networks: Are We Talking About the Same Networks?

International audienceTo appear as a chapter of the Digital STS Handbook (digitalsts.net) This paper discusses the differences and affinities among three types of networks (namely Actor-Networks, Social Networks and Digital Networks) that are playing an increasingly important role in digital STS. In the last few decades, the notion of networks has slowly but steadily struck root across broad strands of STS research. It started with the advent of actor-network theory, which provided a convenient instrument to describe the construction work of socio-technical phenomena. Then came network analysis, and scholars who imported into STS the techniques of investigation and visualization developed in the tradition of social network analysis and scientometrics. Finally, with the increasing 'computerization' of STS, scholars turned their attention to digital networks as a way of tracing collective life. Many researchers have more or less explicitly tried to link these three movements in one coherent set of digital methods, betting on the idea that actor-network theory can be operationalized through network analysis thanks to the data provided by digital networks. Yet, to be honest, the affinity between these three objects is sketchy at best. Besides the homonym 'network', there is little to is little to show for it. Are we sure that we are talking about the same thing? "Odi et amo. quare id faciam, fortasse requiris? nescio, sed fieri sentio et excrucior." Catullus 85 or Carmina LXXXV Professor — you should not confuse the network that is drawn by the description and the network that is used to make the description. Student — …? Professor — But yes! Surely you'd agree that drawing with a pencil is not the same thing as drawing the shape of a pencil. It's the same with this ambiguous word, network. With Actor-Network you may describe something that doesn't at all look like a network — an individual state of mind, a piece of machinery, a fictional character; conversely, you may describe a network — subways, sewages, telephones — which is not all drawn in an 'Actor-Networky' way. You are simply confusing the object with the method. ANT is a method, and mostly a negative one at that; it says nothing about the shape of what is being described with it. Student — This is confusing! But my company executives, are they not forming a nice, revealing, significant network? Professor — Maybe yes, I mean, surely, yes— but so what? Student — Then, I can study them with Actor-Network-Theory

Understanding evolutionary processes during past Quaternary climatic cycles: Can it be applied to the future?

Climate change affected ecological community make-up during the Quaternary which was probably both the cause of, and was caused by, evolutionary processes such as species evolution, adaptation and extinction of species and populations