Cyber Security and Critical Infrastructures

This book contains the manuscripts that were accepted for publication in the MDPI Special Topic "Cyber Security and Critical Infrastructure" after a rigorous peer-review process. Authors from academia, government and industry contributed their innovative solutions, consistent with the interdisciplinary nature of cybersecurity. The book contains 16 articles: an editorial explaining current challenges, innovative solutions, real-world experiences including critical infrastructure, 15 original papers that present state-of-the-art innovative solutions to attacks on critical systems, and a review of cloud, edge computing, and fog's security and privacy issues

Contextual analysis of urban semantics

Dense smart cities are complex environments, characterized by a heterogeneous set of co-varying signals, which constitute urban semantics. We conduct a multivariate analysis to visualize hidden data structure, and propose a research thrust in non-linear dimensional reduction learning technique

Human computer interaction and data visualization

In 2013, SINTEF cited that 90% of the world’s data had been created over the past two years.1 With the onset of Big Data, the ability to analyze data at a rate directly proportional to its collection becomes quite near impossible, albeit nonetheless important. In “Play With Data – An Exploration of Play Analytics and Its Effect on Player Experiences,” Ben Medler explains its pertinence: “Data can be given a different context through relating it to other data. A relation informs someone of how data can be correlated or combined with other data.

Privacy in the Smart City - Applications, Technologies, Challenges and Solutions

Many modern cities strive to integrate information technology into every aspect of city life to create so-called smart cities. Smart cities rely on a large number of application areas and technologies to realize complex interactions between citizens, third parties, and city departments. This overwhelming complexity is one reason why holistic privacy protection only rarely enters the picture. A lack of privacy can result in discrimination and social sorting, creating a fundamentally unequal society. To prevent this, we believe that a better understanding of smart cities and their privacy implications is needed. We therefore systematize the application areas, enabling technologies, privacy types, attackers and data sources for the attacks, giving structure to the fuzzy term “smart city”. Based on our taxonomies, we describe existing privacy-enhancing technologies, review the state of the art in real cities around the world, and discuss promising future research directions. Our survey can serve as a reference guide, contributing to the development of privacy-friendly smart cities

Sustainable metropolitan growth strategies : exploring the role of the built environment

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 138-145).The sustainability of metropolitan areas has been considered one of the most significant social challenges worldwide. Among the various policy options to achieve sustainable metropolitan growth, smart-growth strategies attract increasing interests due to their financial and political feasibility. Leveraging the interconnection between land use and transportation, smart-growth strategies aim to improve urban life and promote sustainability by altering the built environment with such mechanisms as transit-oriented development, mixed-use planning, urban-growth boundary, etc. My focus in this study is to understand the role that the built environment can play in sustainable metropolitan growth. Unlike previous studies that rely primarily on household survey data in the land use-transportation research, I explore the potential for utilizing spatially detailed administrative data to calibrate urban models and support metropolitan planning. I structure this study in three separate essays. In these essays, with several newly available fine-grained administrative datasets and advanced Database Management System (DBMS) and Geographic Information Systems (GIS) tools, I compute a set of improved indicators to characterize the built environment at disaggregated level and incorporate these indicators into quantitative models to investigate the relationships between the built environment, household vehicle usage and residential property values. I select the Boston Metropolitan Area as the study area. The focus of the first essay is to understand the built-environment effect on household vehicle usage as reflected by the millions of odometer readings from annual vehicle safety inspections for all private passenger vehicles registered in the Boston Metropolitan Area. By combining the safety inspection data with fine-grained GIS data layers of common destinations, land use, accessibility, and demographic characteristics, I develop an extensive and spatially detailed analysis of the relationship between annual vehicle miles traveled (VMT) and built-environment characteristics. The empirical results suggest that there are significant associations between built-environment factors and household vehicle usage. In particular, distance to non-work destinations, connectivity, accessibility to transit and jobs play significant roles in explaining the VMT variations. The research findings can help analysts understand the environmental implications of alternative regional development scenarios, and facilitate the dialogue among regional planning agencies, local government and the public regarding sustainable regional development strategies. In the second essay, I investigate the built-environment effect on residential property values with a cross-sectional analysis. The major dataset is the single-family housing transaction records from city and town assessors in the Boston Metropolitan Area assembled by the Warren Group. I use factor analysis to extract several built-environment factors from a large number of built-environment variables, and integrate the factors into hedonic-price models. Spatial econometric techniques are applied to address the spatial autocorrelation. The empirical results suggest that the transaction price of single-family properties is positively associated with accessibility to transit and jobs, connectivity, and walkability, and negatively related to auto dominance. The built-environment effects depend on neighborhood characteristics. In particular, households living in neighborhoods with better transit accessibility tend to pay a higher premium for smart-growth type built-environment features. The research findings suggest that most smart-growth strategies are positively associated with residential property values. Although built-environment characteristics advocated by smart-growth analysts do not have universal appeal to households, they no doubt satisfy an important market segment. In the third essay, I examine the role that selectivity and spatial autocorrelation could play in valuing the built environment. Using transaction and stock data for single-family properties in the City of Boston from 1998 to 2007, I integrate a Heckman-selection model and spatial econometric techniques to account for sample selection and spatial autocorrelation, and estimate the willingness-to-pay for built-environment attributes. The empirical results suggest that the built environment can influence both the probability of sale and transaction price of properties. Failing to correct for sample selection and spatial autocorrelation leads to significant bias in valuing the built-environment. The bias might misguide policy recommendations for intervening urban development patterns and distort estimations of the value-added effect of infrastructure investment for land-value-capture programs.by Diao Mi.Ph.D

Privacy-preserving Payments for Transportation Systems

The operation of our society heavily relies on high mobility of people. Not only our social life but also our economy and trade are built upon a system where people need to be able to move around easily. The costs for building and maintaining a suitable transportation infrastructure to satisfy those needs are high, and to charge users is thus a central requirement. This calls for well functioning payment systems satisfying the multitude of requirements that transportation systems impose on them. Electronic payment systems have many benefits over traditional cash payments as they are easy to maintain, can be more secure, reduce revenue collection costs, and can reduce the execution time of a payment. However, as a drawback, currently employed electronic payment systems usually reveal a payer’s identity during a payment which greatly infringes customer privacy. In the transportation domain this allows to generate fine grain patterns of customers’ locations. Cryptographic payment protocols called e-cash have been proposed which allow to preserve a customer’s privacy. E-cash provides provable guarantees for both security and user privacy, as it allows secure, unlinkable payments which do not reveal the identity of the payer during a payment. From a security and privacy perspective these protocols present a good solution. However, even though e-cash protocols have been proposed three decades ago, there are relatively few actual implementations. One reason for this is their high computational complexity which makes an implementation on potential mobile payment devices rather difficult. While customers usually value their privacy they often do not accept to sacrifice convenience. A fast execution of payments is thus a hard constraint, which conflicts with the computational complexity of e-cash schemes. This dissertation analyzes how e-cash can be used to solve the issue of privacy in the domain of transportation payments while satisfying the unique requirements of transportation payment systems and achieving high security and ease of use. Highlyefficient implementations of the underlying cryptographic primitives of e-cash schemes on constrained devices as they might be used in the transportation setting are presented. Based on the efficient implementations of these primitives, e-cash schemes are analyzed with regards to speed and hardware requirements. The results show that e-cash presents a good solution for privacy-preserving payments in the domain of public transport, if the number of coins that have to be spent can be limited. It is further practically shown that this limitation can be alleviated relying on the e-cash based privacy-preserving pre-payments with refunds scheme (P4R). Moreover, it is demonstrated that the promising feature of supporting the encoding of user attributes into electronic coins can be implemented at only moderate extra cost. Finally, an ecash based e-mobility payment scheme is presented which highlights the flexibility and unique advantages of e-cash based transportation payment schemes

Contributions to Context-Aware Smart Healthcare: A Security and Privacy Perspective

Les tecnologies de la informació i la comunicació han canviat les nostres vides de manera irreversible. La indústria sanitària, una de les indústries més grans i de major creixement, està dedicant molts esforços per adoptar les últimes tecnologies en la pràctica mèdica diària. Per tant, no és sorprenent que els paradigmes sanitaris estiguin en constant evolució cercant serveis més eficients, eficaços i sostenibles. En aquest context, el potencial de la computació ubiqua mitjançant telèfons intel·ligents, rellotges intel·ligents i altres dispositius IoT ha esdevingut fonamental per recopilar grans volums de dades, especialment relacionats amb l'estat de salut i la ubicació de les persones. Les millores en les capacitats de detecció juntament amb l'aparició de xarxes de telecomunicacions d'alta velocitat han facilitat la implementació d'entorns sensibles al context, com les cases i les ciutats intel·ligents, capaços d'adaptar-se a les necessitats dels ciutadans. La interacció entre la computació ubiqua i els entorns sensibles al context va obrir la porta al paradigma de la salut intel·ligent, centrat en la prestació de serveis de salut personalitzats i de valor afegit mitjançant l'explotació de grans quantitats de dades sanitàries, de mobilitat i contextuals. No obstant, la gestió de dades sanitàries, des de la seva recollida fins a la seva anàlisi, planteja una sèrie de problemes desafiants a causa del seu caràcter altament confidencial. Aquesta tesi té per objectiu abordar diversos reptes de seguretat i privadesa dins del paradigma de la salut intel·ligent. Els resultats d'aquesta tesi pretenen ajudar a la comunitat científica a millorar la seguretat dels entorns intel·ligents del futur, així com la privadesa dels ciutadans respecte a les seves dades personals i sanitàries.Las tecnologías de la información y la comunicación han cambiado nuestras vidas de forma irreversible. La industria sanitaria, una de las industrias más grandes y de mayor crecimiento, está dedicando muchos esfuerzos por adoptar las últimas tecnologías en la práctica médica diaria. Por tanto, no es sorprendente que los paradigmas sanitarios estén en constante evolución en busca de servicios más eficientes, eficaces y sostenibles. En este contexto, el potencial de la computación ubicua mediante teléfonos inteligentes, relojes inteligentes, dispositivos wearables y otros dispositivos IoT ha sido fundamental para recopilar grandes volúmenes de datos, especialmente relacionados con el estado de salud y la localización de las personas. Las mejoras en las capacidades de detección junto con la aparición de redes de telecomunicaciones de alta velocidad han facilitado la implementación de entornos sensibles al contexto, como las casas y las ciudades inteligentes, capaces de adaptarse a las necesidades de los ciudadanos. La interacción entre la computación ubicua y los entornos sensibles al contexto abrió la puerta al paradigma de la salud inteligente, centrado en la prestación de servicios de salud personalizados y de valor añadido mediante la explotación significativa de grandes cantidades de datos sanitarios, de movilidad y contextuales. No obstante, la gestión de datos sanitarios, desde su recogida hasta su análisis, plantea una serie de cuestiones desafiantes debido a su naturaleza altamente confidencial. Esta tesis tiene por objetivo abordar varios retos de seguridad y privacidad dentro del paradigma de la salud inteligente. Los resultados de esta tesis pretenden ayudar a la comunidad científica a mejorar la seguridad de los entornos inteligentes del futuro, así como la privacidad de los ciudadanos con respecto a sus datos personales y sanitarios.Information and communication technologies have irreversibly changed our lives. The healthcare industry, one of the world’s largest and fastest-growing industries, is dedicating many efforts in adopting the latest technologies into daily medical practice. It is not therefore surprising that healthcare paradigms are constantly evolving seeking for more efficient, effective and sustainable services. In this context, the potential of ubiquitous computing through smartphones, smartwatches, wearables and IoT devices has become fundamental to collect large volumes of data, including people's health status and people’s location. The enhanced sensing capabilities together with the emergence of high-speed telecommunication networks have facilitated the implementation of context-aware environments, such as smart homes and smart cities, able to adapt themselves to the citizens needs. The interplay between ubiquitous computing and context-aware environments opened the door to the so-called smart health paradigm, focused on the provision of added-value personalised health services by meaningfully exploiting vast amounts of health, mobility and contextual data. However, the management of health data, from their gathering to their analysis, arises a number of challenging issues due to their highly confidential nature. In particular, this dissertation addresses several security and privacy challenges within the smart health paradigm. The results of this dissertation are intended to help the research community to enhance the security of the intelligent environments of the future as well as the privacy of the citizens regarding their personal and health data