Security in Cloud Computing: Evaluation and Integration

Au cours de la dernière décennie, le paradigme du Cloud Computing a révolutionné la manière dont nous percevons les services de la Technologie de l’Information (TI). Celui-ci nous a donné l’opportunité de répondre à la demande constamment croissante liée aux besoins informatiques des usagers en introduisant la notion d’externalisation des services et des données. Les consommateurs du Cloud ont généralement accès, sur demande, à un large éventail bien réparti d’infrastructures de TI offrant une pléthore de services. Ils sont à même de configurer dynamiquement les ressources du Cloud en fonction des exigences de leurs applications, sans toutefois devenir partie intégrante de l’infrastructure du Cloud. Cela leur permet d’atteindre un degré optimal d’utilisation des ressources tout en réduisant leurs coûts d’investissement en TI. Toutefois, la migration des services au Cloud intensifie malgré elle les menaces existantes à la sécurité des TI et en crée de nouvelles qui sont intrinsèques à l’architecture du Cloud Computing. C’est pourquoi il existe un réel besoin d’évaluation des risques liés à la sécurité du Cloud durant le procédé de la sélection et du déploiement des services. Au cours des dernières années, l’impact d’une efficace gestion de la satisfaction des besoins en sécurité des services a été pris avec un sérieux croissant de la part des fournisseurs et des consommateurs. Toutefois, l’intégration réussie de l’élément de sécurité dans les opérations de la gestion des ressources du Cloud ne requiert pas seulement une recherche méthodique, mais aussi une modélisation méticuleuse des exigences du Cloud en termes de sécurité. C’est en considérant ces facteurs que nous adressons dans cette thèse les défis liés à l’évaluation de la sécurité et à son intégration dans les environnements indépendants et interconnectés du Cloud Computing. D’une part, nous sommes motivés à offrir aux consommateurs du Cloud un ensemble de méthodes qui leur permettront d’optimiser la sécurité de leurs services et, d’autre part, nous offrons aux fournisseurs un éventail de stratégies qui leur permettront de mieux sécuriser leurs services d’hébergements du Cloud. L’originalité de cette thèse porte sur deux aspects : 1) la description innovatrice des exigences des applications du Cloud relativement à la sécurité ; et 2) la conception de modèles mathématiques rigoureux qui intègrent le facteur de sécurité dans les problèmes traditionnels du déploiement des applications, d’approvisionnement des ressources et de la gestion de la charge de travail au coeur des infrastructures actuelles du Cloud Computing. Le travail au sein de cette thèse est réalisé en trois phases.----------ABSTRACT: Over the past decade, the Cloud Computing paradigm has revolutionized the way we envision IT services. It has provided an opportunity to respond to the ever increasing computing needs of the users by introducing the notion of service and data outsourcing. Cloud consumers usually have online and on-demand access to a large and distributed IT infrastructure providing a plethora of services. They can dynamically configure and scale the Cloud resources according to the requirements of their applications without becoming part of the Cloud infrastructure, which allows them to reduce their IT investment cost and achieve optimal resource utilization. However, the migration of services to the Cloud increases the vulnerability to existing IT security threats and creates new ones that are intrinsic to the Cloud Computing architecture, thus the need for a thorough assessment of Cloud security risks during the process of service selection and deployment. Recently, the impact of effective management of service security satisfaction has been taken with greater seriousness by the Cloud Service Providers (CSP) and stakeholders. Nevertheless, the successful integration of the security element into the Cloud resource management operations does not only require methodical research, but also necessitates the meticulous modeling of the Cloud security requirements. To this end, we address throughout this thesis the challenges to security evaluation and integration in independent and interconnected Cloud Computing environments. We are interested in providing the Cloud consumers with a set of methods that allow them to optimize the security of their services and the CSPs with a set of strategies that enable them to provide security-aware Cloud-based service hosting. The originality of this thesis lies within two aspects: 1) the innovative description of the Cloud applications’ security requirements, which paved the way for an effective quantification and evaluation of the security of Cloud infrastructures; and 2) the design of rigorous mathematical models that integrate the security factor into the traditional problems of application deployment, resource provisioning, and workload management within current Cloud Computing infrastructures. The work in this thesis is carried out in three phases

Safe Reinforcement Learning via Observation Shielding

Reinforcement Learning (RL) algorithms have shown success in scaling up to large problems. However, deploying those algorithms in real-world applications remains challenging due to their vulnerability to adversarial perturbations. Existing RL robustness methods against adversarial attacks are weak to large perturbations - a scenario that cannot be ruled out for RL adversarial threats, as is the case for deep neural networks in classification tasks. This paper proposes a method called observation-shielding RL (OSRL) to increase the robustness of RL against large perturbations using predictive models and threat detection. Instead of changing the RL algorithms with robustness regularization or retrain them with adversarial perturbations, we depart considerably from previous approaches and develop an add-on safety feature for existing RL algorithms during runtime. OSRL builds on the idea of model predictive shielding, where an observation predictive model is used to override the perturbed observations as needed to ensure safety. Extensive experiments on various MuJoCo environments (Ant, Hooper) and the classical pendulum environment demonstrate that our proposed OSRL is safer and more efficient than state-of-the-art robustness methods under large perturbations

The Epidemiology and Outcome of Biliary Atresia: Saudi Arabian National Study (2000–2018)

BackgroundThe epidemiology and outcomes of biliary atresia (BA) have been well-documented in national cohorts from two main ethnicities, namely, the Asian Orientals and Caucasians, with incidence ranging from 1 in 5,000 to 1 in 9,000 live births in East Asia and 1 in 15,000 to 19,000 live births in Europe and North America.ObjectiveWe report the first nationwide BA study outside North America, Europe, and East Asia to describe the epidemiology and outcomes of BA in Saudi Arabia.MethodsA national database of BA cases diagnosed between 2000 and 2018 was analyzed. We assessed clearance of jaundice (bilirubin <20 μmol/L) in all cases that underwent Kasai portoenterostomy (KPE). We then estimated survival using the Kaplan–Meier method with endpoints of liver transplantation (LT), death, or survival with native liver (SNL).ResultsBA was diagnosed in 204 infants (106 females; 10% pre-term). The incidence of BA was 1 in 44,365, or 2.254 in 100,000 live births (range, 0.5–4 in 100,000). Polysplenia was diagnosed in 22 cases (11%). The median age at referral was 65 days. A total of 146 children (71.5%) underwent KPE at a median age of 70 days. Clearance of jaundice was achieved in 66 of the 146 (45%) infants. The 10-year SNL after KPE was 25.5%, and the overall 10-year estimated survival was 72.5%. The Kaplan–Meier survival curves for patients undergoing KPE at the age of <60, 61–90, and >90 days showed a SNL rate at 51.6, 33, and 12.5%, respectively, at 5 years (P < 0.001). The 2-, 5-, and 10-year post-LT survival rates were 92.5, 90.6, and 90%, respectively. Undergoing an initial KPE did not impact negatively on the overall LT survival rate when compared to BA cases that underwent primary LT (P = 0.88).ConclusionThe incidence rate of BA in Saudi Arabia is lower than the incidence reported elsewhere. Late referral of BA cases remains a problem in Saudi Arabia; as a result, the SNL rate was lower than reported by other national registries. Hence, national policies devoted to timely referral and earlier age at KPE are needed