The Role of a Microservice Architecture on cybersecurity and operational resilience in critical systems

Critical systems are characterized by their high degree of intolerance to threats, in other words, their high level of resilience, because depending on the context in which the system is inserted, the slightest failure could imply significant damage, whether in economic terms, or loss of reputation, of information, of infrastructure, of the environment, or human life. The security of such systems is traditionally associated with legacy infrastructures and data centers that are monolithic, which translates into increasingly high evolution and protection challenges. In the current context of rapid transformation where the variety of threats to systems has been consistently increasing, this dissertation aims to carry out a compatibility study of the microservice architecture, which is denoted by its characteristics such as resilience, scalability, modifiability and technological heterogeneity, being flexible in structural adaptations, and in rapidly evolving and highly complex settings, making it suited for agile environments. It also explores what response artificial intelligence, more specifically machine learning, can provide in a context of security and monitorability when combined with a simple banking system that adopts the microservice architecture.Os sistemas críticos são caracterizados pelo seu elevado grau de intolerância às ameaças, por outras palavras, o seu alto nível de resiliência, pois dependendo do contexto onde se insere o sistema, a mínima falha poderá implicar danos significativos, seja em termos económicos, de perda de reputação, de informação, de infraestrutura, de ambiente, ou de vida humana. A segurança informática de tais sistemas está tradicionalmente associada a infraestruturas e data centers legacy, ou seja, de natureza monolítica, o que se traduz em desafios de evolução e proteção cada vez mais elevados. No contexto atual de rápida transformação, onde as variedades de ameaças aos sistemas têm vindo consistentemente a aumentar, esta dissertação visa realizar um estudo de compatibilidade da arquitetura de microserviços, que se denota pelas suas caraterísticas tais como a resiliência, escalabilidade, modificabilidade e heterogeneidade tecnológica, sendo flexível em adaptações estruturais, e em cenários de rápida evolução e elevada complexidade, tornando-a adequada a ambientes ágeis. Explora também a resposta que a inteligência artificial, mais concretamente, machine learning, pode dar num contexto de segurança e monitorabilidade quando combinado com um simples sistema bancário que adota uma arquitetura de microserviços

Big Data and Large-scale Data Analytics: Efficiency of Sustainable Scalability and Security of Centralized Clouds and Edge Deployment Architectures

One of the significant shifts of the next-generation computing technologies will certainly be in the development of Big Data (BD) deployment architectures. Apache Hadoop, the BD landmark, evolved as a widely deployed BD operating system. Its new features include federation structure and many associated frameworks, which provide Hadoop 3.x with the maturity to serve different markets. This dissertation addresses two leading issues involved in exploiting BD and large-scale data analytics realm using the Hadoop platform. Namely, (i)Scalability that directly affects the system performance and overall throughput using portable Docker containers. (ii) Security that spread the adoption of data protection practices among practitioners using access controls. An Enhanced Mapreduce Environment (EME), OPportunistic and Elastic Resource Allocation (OPERA) scheduler, BD Federation Access Broker (BDFAB), and a Secure Intelligent Transportation System (SITS) of multi-tiers architecture for data streaming to the cloud computing are the main contribution of this thesis study

Systemunterstützung für moderne Speichertechnologien

Trust and scalability are the two significant factors which impede the dissemination of clouds. The possibility of privileged access to customer data by a cloud provider limits the usage of clouds for processing security-sensitive data. Low latency cloud services rely on in-memory computations, and thus, are limited by several characteristics of Dynamic RAM (DRAM) such as capacity, density, energy consumption, for example. Two technological areas address these factors. Mainstream server platforms, such as Intel Software Guard eXtensions (SGX) und AMD Secure Encrypted Virtualisation (SEV) offer extensions for trusted execution in untrusted environments. Various technologies of Non-Volatile RAM (NV-RAM) have better capacity and density compared to DRAM and thus can be considered as DRAM alternatives in the future. However, these technologies and extensions require new programming approaches and system support since they add features to the system architecture: new system components (Intel SGX) and data persistence (NV-RAM). This thesis is devoted to the programming and architectural aspects of persistent and trusted systems. For trusted systems, an in-depth analysis of new architectural extensions was performed. A novel framework named EActors and a database engine named STANlite were developed to effectively use the capabilities of trusted~execution. For persistent systems, an in-depth analysis of prospective memory technologies, their features and the possible impact on system architecture was performed. A new persistence model, called the hypervisor-based model of persistence, was developed and evaluated by the NV-Hypervisor. This offers transparent persistence for legacy and proprietary software, and supports virtualisation of persistent memory.Vertrauenswürdigkeit und Skalierbarkeit sind die beiden maßgeblichen Faktoren, die die Verbreitung von Clouds behindern. Die Möglichkeit privilegierter Zugriffe auf Kundendaten durch einen Cloudanbieter schränkt die Nutzung von Clouds bei der Verarbeitung von sicherheitskritischen und vertraulichen Informationen ein. Clouddienste mit niedriger Latenz erfordern die Durchführungen von Berechnungen im Hauptspeicher und sind daher an Charakteristika von Dynamic RAM (DRAM) wie Kapazität, Dichte, Energieverbrauch und andere Aspekte gebunden. Zwei technologische Bereiche befassen sich mit diesen Faktoren: Etablierte Server Plattformen wie Intel Software Guard eXtensions (SGX) und AMD Secure Encrypted Virtualisation (SEV) stellen Erweiterungen für vertrauenswürdige Ausführung in nicht vertrauenswürdigen Umgebungen bereit. Verschiedene Technologien von nicht flüchtigem Speicher bieten bessere Kapazität und Speicherdichte verglichen mit DRAM, und können daher in Zukunft als Alternative zu DRAM herangezogen werden. Jedoch benötigen diese Technologien und Erweiterungen neuartige Ansätze und Systemunterstützung bei der Programmierung, da diese der Systemarchitektur neue Funktionalität hinzufügen: Systemkomponenten (Intel SGX) und Persistenz (nicht-flüchtiger Speicher). Diese Dissertation widmet sich der Programmierung und den Architekturaspekten von persistenten und vertrauenswürdigen Systemen. Für vertrauenswürdige Systeme wurde eine detaillierte Analyse der neuen Architekturerweiterungen durchgeführt. Außerdem wurden das neuartige EActors Framework und die STANlite Datenbank entwickelt, um die neuen Möglichkeiten von vertrauenswürdiger Ausführung effektiv zu nutzen. Darüber hinaus wurde für persistente Systeme eine detaillierte Analyse zukünftiger Speichertechnologien, deren Merkmale und mögliche Auswirkungen auf die Systemarchitektur durchgeführt. Ferner wurde das neue Hypervisor-basierte Persistenzmodell entwickelt und mittels NV-Hypervisor ausgewertet, welches transparente Persistenz für alte und proprietäre Software, sowie Virtualisierung von persistentem Speicher ermöglicht