Overcoming Data Breaches and Human Factors in Minimizing Threats to Cyber-Security Ecosystems

This mixed-methods study focused on the internal human factors responsible for data breaches that could cause adverse impacts on organizations. Based on the Swiss cheese theory, the study was designed to examine preventative measures that managers could implement to minimize potential data breaches resulting from internal employees\u27 behaviors. The purpose of this study was to provide insight to managers about developing strategies that could prevent data breaches from cyber-threats by focusing on the specific internal human factors responsible for data breaches, the root causes, and the preventive measures that could minimize threats from internal employees. Data were collected from 10 managers and 12 employees from the business sector, and 5 government managers in Ivory Coast, Africa. The mixed methodology focused on the why and who using the phenomenological approach, consisting of a survey, face-to-face interviews using open-ended questions, and a questionnaire to extract the experiences and perceptions of the participants about preventing the adverse consequences from cyber-threats. The results indicated the importance of top managers to be committed to a coordinated, continuous effort throughout the organization to ensure cyber security awareness, training, and compliance of security policies and procedures, as well as implementing and upgrading software designed to detect and prevent data breaches both internally and externally. The findings of this study could contribute to social change by educating managers about preventing data breaches who in turn may implement information accessibility without retribution. Protecting confidential data is a major concern because one data breach could impact many people as well as jeopardize the viability of the entire organization

A new Caesium quantum gas microscope with precise magnetic field control

In dieser Arbeit wird der Aufbau eines neuen Experiments mit ultrakalten Quantengasen, sowie der aktuelle Stand der Experimente beschrieben. Das neu aufgebaute Experiment verwendet Cäsium aufgrund seiner günstigen atomaren Eigenschaften. Verschiedene Feshbach-Resonanzen bei niedrigen Magnetfeldern können genutzt werden, um die Streueigenschaften zu kontrollieren. Die große Feinstrukturaufspaltung ermöglicht die effiziente Umsetzung einer neuen Methode zur Erzeugung künstlicher Eichfelder unter Verwendung eines zustandsabhängigen Gitters. Ein integriertes Quantengasmikroskop ermöglicht die ortsaufgelöste Abbildung der erzeugten Systeme und kann zur lokalen Adressierung genutzt werden. Ein wesentliches Werkzeug für die geplante Methode zur Erzeugung künstlicher Eichfelder ist die präzise Kontrolle über die Magnetfelder und Gradienten. Mit Hilfe mehrerer Spulenpaare entlang aller drei Raumachsen können Magnetfelder bis zu 200 G und 100 G cm−1 in jeder möglichen Orientierung der Quantisierungsachse erzeugt werden. Eine aktive Magnetfeldstabilisierung wurde integriert, um Fluktuationen des Hintergrundmagnetfeldes in den horizontalen Achsen unabhängig vom erzeugten Experimentfeld zu unterdrücken. Das System wurde mittels Mikrowellenspektroskopie charakterisiert, wobei absolute Stabilitäten von 110 µG nachgewiesen werden konnten. Eine speziell entwickelte Anordnung um die Glaszelle herum kombiniert hochauflösende Bildgebung und Magnetfeldkontrolle in einem kompakten Design und bietet gleichzeitig maximalen optischen Zugang. Nach einer ersten Kühlungsphase werden die Atome optisch in die Glaszelle transportiert, wo sie weiter abgekühlt werden, bis sie quantenentartet sind. Das erzeugte Bose-Einstein-Kondensat (BEC) wird mit Hilfe eines vertikalen Gitters mit großen Abständen zu einem zweidimensionalen System komprimiert und in ein quadratisches optisches Gitter geladen. Mott-Isolator (MI) Zustände mit homogener Dichte werden als Ausgangspunkt für zukünftige Experimente erzeugt. Zusätzliche Gitterstrahlen mit doppelter Periodizität auf jeder Achse schaffen ein Supergitter und erweitern die Möglichkeiten der Zustandsvorbereitung und Messung. Das in dieser Arbeit beschriebene Experiment wird die Untersuchung von topologischen Vielteilchenzuständen ermöglichen.In this work the construction of a new ultracold quantum gas experiment and the current status of experiments is described. The newly constructed experiment uses Caesium due to its favourable atomic properties. Various Feshbach resonances at low magnetic fields can be used to control the scattering properties. The large fine-structure splitting will allow for the efficient implementation of a new method to create artificial gauge fields using a state-dependent lattice. An integrated quantum gas microscope allows site-resolved imaging of the created systems and can be used for local addressing. An essential tool for the planned method to create artificial gauge fields is the precise control over the magnetic fields and gradients. Using multiple coil pairs along all three axes magnetic fields up to 200 G and 100 G cm−1 can be generated in any possible orientation of the quantisation axis. An active stabilisation system was integrated to suppress fluctuations of the background magnetic field in the horizontal axes independent of the applied experiment fields. The system was characterised using microwave spectroscopy, demonstrating absolute stabilities of 110 µG root-mean-square (rms). A specially designed assembly around the glass cell combines high-resolution imaging and magnetic field control in a compact design, while providing maximal optical access. After a pre-cooling stage the atoms are transported optically into the science chamber, where they are cooled further until they become quantum degenerate. The generated Bose-Einstein condensate (BEC) is compressed into a 2d system using a large-spacing vertical lattice and loaded into an optical square lattice. Mott-insulator (MI) states with homogeneous density are created as starting point for future experiments. Additional lattice beams with twice the periodicity at each axis create a super-lattice, extending the capabilities for state preparation and read-out. The experiment described in this thesis will allow for the study of topological many-body phases

Development and management of collective network and cloud computing infrastructures

In the search and development of more participatory models for infrastructure development and management, in this dissertation, we investigate models for the financing, deployment, and operation of network and cloud computing infrastructures. Our main concern is to overcome the inherent exclusion in participation in the processes of development and management and in the right of use in the current dominant models. Our work starts by studying in detail the model of Guifi.net, a successful bottom-up initiative for building network infrastructure, generally referred to as a community networks. We pay special attention to its governance system and economic organisation because we argue that these are the key components of the success of this initiative. Then, we generalise our findings for any community network, aiming at becoming sustainable and scalable, and we explore the suitability of the Guifi.net model to the cloud computing infrastructure. As a result of both, we coin the attribute extensible to refer to infrastructure that is relatively easy to expand and maintain in contrast to those naturally limited or hard to expand, such as natural resources or highly complex or advanced artificial systems. We conclude proposing a generic model which, in our opinion, is suitable, at least, for managing extensible infrastructure. The Guifi.net model is deeply rooted in the commons; thus, the research in this field, in general, and Elinor Ostrom’s work, in particular, have left a profound imprint in our work. Our results show that the \guifinet model meets almost entirely the principles of long-enduring commons identified by E. Ostrom. This work has been developed as an industrial doctorate. As such, it combines academic research with elements of practice and pursues an effective knowledge transfer between academia and the private sector. Given that the private sector’s partner is a not-for-profit organisation, the effort to create social value has prevailed over the ambition to advance the development of a specific industrial product or particular technology.En la recerca i desenvolupament de models més participatius per al desenvolupament i gestió d'infraestructura, en aquesta tesi investiguem sobre models per al finançament, desplegament i operació d'infraestructures de xarxa i de computació al núvol. La nostra preocupació principal és fer front a l’exclusió inherent dels models dominants actualment pel que fa a la participació en els processos de desenvolupament i gestió i, també, als drets d’us. El nostre treball comença amb un estudi detallat del model de Guifi.net, un cas d'èxit d'iniciativa ciutadana en la construcció d'infraestructura de xarxa, iniciatives que es coneixen com a xarxes comunitàries. En fer-ho, parem una atenció especial al sistema de governança i a l’organització econòmica perquè pensem que són els dos elements claus de l'èxit d'aquesta iniciativa. Tot seguit passem a analitzar d'altres xarxes comunitàries per abundar en la comprensió dels factors determinants per a la seva sostenibilitat i escalabilitat. Després ampliem el nostre estudi analitzant la capacitat i el comportament del model de Guifi.net en el camp de les infraestructures de computació al núvol. A resultes d'aquests estudis, proposem l'atribut extensible per a descriure aquelles infraestructures que són relativament fàcil d'ampliar i gestionar, en contraposició a les que o bé estan limitades de forma natural o be són difícils d'ampliar, com ara els recursos naturals o els sistemes artificials avançats o complexos. Finalitzem aquest treball fent una proposta de model genèric que pensem que és d'aplicabilitat, com a mínim, a tot tipus d'infraestructura extensible. El model de Guifi.net està fortament vinculat als bens comuns. És per això que la recerca en aquest àmbit, en general, i els treballs de Elinor Ostrom en particular, han deixat una forta empremta en el nostre treball. Els resultats que hem obtingut mostren que el model Guifi.net s'ajusta molt bé als principis que segons Ostrom han de complir els béns comuns per ser sostenibles. Aquest treball s'ha desenvolupat com a doctorat industrial. Com a tal, combina la investigació acadèmica amb elements de practica i persegueix una transferència efectiva de coneixement entre l'àmbit acadèmic i el sector privat. Ates que el soci del sector privat és una organització sense ànim de lucre, l’esforç per crear valor social ha prevalgut en l’ambició d’avançar en el desenvolupament d'un producte industrial específic o d'una tecnologia particula

Development and management of collective network and cloud computing infrastructures

Pla de Doctorat industrial de la Generalitat de CatalunyaIn the search and development of more participatory models for infrastructure development and management, in this dissertation, we investigate models for the financing, deployment, and operation of network and cloud computing infrastructures. Our main concern is to overcome the inherent exclusion in participation in the processes of development and management and in the right of use in the current dominant models. Our work starts by studying in detail the model of Guifi.net, a successful bottom-up initiative for building network infrastructure, generally referred to as a community networks. We pay special attention to its governance system and economic organisation because we argue that these are the key components of the success of this initiative. Then, we generalise our findings for any community network, aiming at becoming sustainable and scalable, and we explore the suitability of the Guifi.net model to the cloud computing infrastructure. As a result of both, we coin the attribute extensible to refer to infrastructure that is relatively easy to expand and maintain in contrast to those naturally limited or hard to expand, such as natural resources or highly complex or advanced artificial systems. We conclude proposing a generic model which, in our opinion, is suitable, at least, for managing extensible infrastructure. The Guifi.net model is deeply rooted in the commons; thus, the research in this field, in general, and Elinor Ostrom’s work, in particular, have left a profound imprint in our work. Our results show that the \guifinet model meets almost entirely the principles of long-enduring commons identified by E. Ostrom. This work has been developed as an industrial doctorate. As such, it combines academic research with elements of practice and pursues an effective knowledge transfer between academia and the private sector. Given that the private sector’s partner is a not-for-profit organisation, the effort to create social value has prevailed over the ambition to advance the development of a specific industrial product or particular technology.En la recerca i desenvolupament de models més participatius per al desenvolupament i gestió d'infraestructura, en aquesta tesi investiguem sobre models per al finançament, desplegament i operació d'infraestructures de xarxa i de computació al núvol. La nostra preocupació principal és fer front a l’exclusió inherent dels models dominants actualment pel que fa a la participació en els processos de desenvolupament i gestió i, també, als drets d’us. El nostre treball comença amb un estudi detallat del model de Guifi.net, un cas d'èxit d'iniciativa ciutadana en la construcció d'infraestructura de xarxa, iniciatives que es coneixen com a xarxes comunitàries. En fer-ho, parem una atenció especial al sistema de governança i a l’organització econòmica perquè pensem que són els dos elements claus de l'èxit d'aquesta iniciativa. Tot seguit passem a analitzar d'altres xarxes comunitàries per abundar en la comprensió dels factors determinants per a la seva sostenibilitat i escalabilitat. Després ampliem el nostre estudi analitzant la capacitat i el comportament del model de Guifi.net en el camp de les infraestructures de computació al núvol. A resultes d'aquests estudis, proposem l'atribut extensible per a descriure aquelles infraestructures que són relativament fàcil d'ampliar i gestionar, en contraposició a les que o bé estan limitades de forma natural o be són difícils d'ampliar, com ara els recursos naturals o els sistemes artificials avançats o complexos. Finalitzem aquest treball fent una proposta de model genèric que pensem que és d'aplicabilitat, com a mínim, a tot tipus d'infraestructura extensible. El model de Guifi.net està fortament vinculat als bens comuns. És per això que la recerca en aquest àmbit, en general, i els treballs de Elinor Ostrom en particular, han deixat una forta empremta en el nostre treball. Els resultats que hem obtingut mostren que el model Guifi.net s'ajusta molt bé als principis que segons Ostrom han de complir els béns comuns per ser sostenibles. Aquest treball s'ha desenvolupat com a doctorat industrial. Com a tal, combina la investigació acadèmica amb elements de practica i persegueix una transferència efectiva de coneixement entre l'àmbit acadèmic i el sector privat. Ates que el soci del sector privat és una organització sense ànim de lucre, l’esforç per crear valor social ha prevalgut en l’ambició d’avançar en el desenvolupament d'un producte industrial específic o d'una tecnologia particularPostprint (published version

Advances in Information Security and Privacy

With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue

Computation offloading for fast and energy-efficient edge computing

In recent years, the demand for computing power has increased considerably due to the popularity of applications that involve computationally intensive tasks such as machine learning or computer vision. At the same time, users increasingly run such applications on smartphones or wearables, which have limited computational power. The research community has proposed computation offloading to meet the demand for computing power. Resource-constrained devices offload workload to remote resource providers. These providers perform the computations and return the results via the network. Computation offloading has two major benefits. First, it accelerates the execution of computationally intensive tasks and therefore reduces waiting times. Second, it decreases the energy consumption of the offloading device, which is especially attractive for devices that run on battery. After years in which cloud servers were the primary resource providers, computation offloading in edge computing systems is currently gaining popularity. Edge-based systems leverage end-user devices such as smartphones, laptops, or desktop PCs instead of cloud servers as computational resource providers. Computation offloading in such environments leads to lower latencies, better utilization of end-user devices, and lower costs in comparison to traditional cloud computing. In this thesis, we present a computation offloading approach for fast and energy-efficient edge computing. We build upon the Tasklet system – a middleware-based computation offloading system. The Tasklet system allows devices to offload heterogeneous tasks to heterogeneous providers. We address three challenges of computation offloading in the edge. First, many applications are data-intensive, which necessitates a time-consuming transfer of input data ahead of a remote execution. To overcome this challenge, we introduce DataVinci – an approach that proactively places input data on suitable devices to accelerate task execution. DataVinci additionally offers task placement strategies that exploit data locality. Second, modern applications are often user-facing and responsive. They require sub-second execution of computationally intensive tasks to ensure proper user experience. We design the decentralized scheduling approach DecArt for such applications. Third, deciding whether a local or remote execution of an upcoming task will consume less energy is non-trivial. This decision is particularly challenging as task complexity and result data size vary across executions, even if the source code is similar. We introduce the energy-aware scheduling approach Voltaire, which uses machine learning and device-specific energy profiles for making precise offloading decisions. We integrate DataVinci, DecArt, and Voltaire into the Tasklet system and evaluate the benefits in extensive experiments

Security of Cyber-Physical Systems

Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

ANOMALY INFERENCE BASED ON HETEROGENEOUS DATA SOURCES IN AN ELECTRICAL DISTRIBUTION SYSTEM

Harnessing the heterogeneous data sets would improve system observability. While the current metering infrastructure in distribution network has been utilized for the operational purpose to tackle abnormal events, such as weather-related disturbance, the new normal we face today can be at a greater magnitude. Strengthening the inter-dependencies as well as incorporating new crowd-sourced information can enhance operational aspects such as system reconfigurability under extreme conditions. Such resilience is crucial to the recovery of any catastrophic events. In this dissertation, it is focused on the anomaly of potential foul play within an electrical distribution system, both primary and secondary networks as well as its potential to relate to other feeders from other utilities. The distributed generation has been part of the smart grid mission, the addition can be prone to electronic manipulation. This dissertation provides a comprehensive establishment in the emerging platform where the computing resources have been ubiquitous in the electrical distribution network. The topics covered in this thesis is wide-ranging where the anomaly inference includes load modeling and profile enhancement from other sources to infer of topological changes in the primary distribution network. While metering infrastructure has been the technological deployment to enable remote-controlled capability on the dis-connectors, this scholarly contribution represents the critical knowledge of new paradigm to address security-related issues, such as, irregularity (tampering by individuals) as well as potential malware (a large-scale form) that can massively manipulate the existing network control variables, resulting into large impact to the power grid

Energy Efficient Servers

Computer scienc