Infrastructural Security for Virtualized Grid Computing

The goal of the grid computing paradigm is to make computer power as easy to access as an electrical power grid. Unlike the power grid, the computer grid uses remote resources located at a service provider. Malicious users can abuse the provided resources, which not only affects their own systems but also those of the provider and others. Resources are utilized in an environment where sensitive programs and data from competitors are processed on shared resources, creating again the potential for misuse. This is one of the main security issues, since in a business environment competitors distrust each other, and the fear of industrial espionage is always present. Currently, human trust is the strategy used to deal with these threats. The relationship between grid users and resource providers ranges from highly trusted to highly untrusted. This wide trust relationship occurs because grid computing itself changed from a research topic with few users to a widely deployed product that included early commercial adoption. The traditional open research communities have very low security requirements, while in contrast, business customers often operate on sensitive data that represents intellectual property; thus, their security demands are very high. In traditional grid computing, most users share the same resources concurrently. Consequently, information regarding other users and their jobs can usually be acquired quite easily. This includes, for example, that a user can see which processes are running on another user´s system. For business users, this is unacceptable since even the meta-data of their jobs is classified. As a consequence, most commercial customers are not convinced that their intellectual property in the form of software and data is protected in the grid. This thesis proposes a novel infrastructural security solution that advances the concept of virtualized grid computing. The work started back in 2007 and led to the development of the XGE, a virtual grid management software. The XGE itself uses operating system virtualization to provide a virtualized landscape. Users’ jobs are no longer executed in a shared manner; they are executed within special sandboxed environments. To satisfy the requirements of a traditional grid setup, the solution can be coupled with an installed scheduler and grid middleware on the grid head node. To protect the prominent grid head node, a novel dual-laned demilitarized zone is introduced to make attacks more difficult. In a traditional grid setup, the head node and the computing nodes are installed in the same network, so a successful attack could also endanger the user´s software and data. While the zone complicates attacks, it is, as all security solutions, not a perfect solution. Therefore, a network intrusion detection system is enhanced with grid specific signatures. A novel software called Fence is introduced that supports end-to-end encryption, which means that all data remains encrypted until it reaches its final destination. It transfers data securely between the user´s computer, the head node and the nodes within the shielded, internal network. A lightweight kernel rootkit detection system assures that only trusted kernel modules can be loaded. It is no longer possible to load untrusted modules such as kernel rootkits. Furthermore, a malware scanner for virtualized grids scans for signs of malware in all running virtual machines. Using virtual machine introspection, that scanner remains invisible for most types of malware and has full access to all system calls on the monitored system. To speed up detection, the load is distributed to multiple detection engines simultaneously. To enable multi-site service-oriented grid applications, the novel concept of public virtual nodes is presented. This is a virtualized grid node with a public IP address shielded by a set of dynamic firewalls. It is possible to create a set of connected, public nodes, either present on one or more remote grid sites. A special web service allows users to modify their own rule set in both directions and in a controlled manner. The main contribution of this thesis is the presentation of solutions that convey the security of grid computing infrastructures. This includes the XGE, a software that transforms a traditional grid into a virtualized grid. Design and implementation details including experimental evaluations are given for all approaches. Nearly all parts of the software are available as open source software. A summary of the contributions and an outlook to future work conclude this thesis

Sécurité et protection de la vie privée dans les systèmes embarqués automobiles

Electronic equipment has become an integral part of a vehicle's network architecture, which consists of multiple buses and microcontrollers called Electronic Control Units (ECUs). These ECUs recently also connect to the outside world. Navigation and entertainment system, consumer devices, and Car2X functions are examples for this. Recent security analyses have shown severe vulnerabilities of exposed ECUs and protocols, which may make it possible for attackers to gain control over a vehicle. Given that car safety-critical systems can no longer be fully isolated from such third party devices and infotainment services, we propose a new approach to securing vehicular on-board systems that combines mechanisms at different layers of the communication stack and of the execution platforms. We describe our secure communication protocols, which are designed to provide strong cryptographic assurances together with an efficient implementation fitting the prevalent vehicular communication paradigms. They rely on hardware security modules providing secure storage and acting as root of trust. A distributed data flow tracking based approach is employed for checking code execution against a security policy describing authorized communication patterns. Binary instrumentation is used to track data flows throughout execution (taint engine) and also between control units (middleware), thus making it applicable to industrial applications. We evaluate the feasibility of our mechanisms to secure communication on the CAN bus, which is ubiquitously implemented in cars today. A proof of concept demonstrator also shows the feasibility of integrating security features into real vehicles.L'équipement électronique de bord est maintenant devenue partie intégrante de l'architecture réseau des véhicules. Elle s’appuie sur l'interconnexion de microcontroleurs appelés ECUs par des bus divers. On commence maintenant à connecter ces ECUs au monde extérieur, comme le montrent les systèmes de navigation, de divertissement, ou de communication mobile embarqués, et les fonctionnalités Car2X. Des analyses récentes ont montré de graves vulnérabilités des ECUs et protocoles employés qui permettent à un attaquant de prendre le contrôle du véhicule. Comme les systèmes critiques du véhicule ne peuvent plus être complètement isolés, nous proposons une nouvelle approche pour sécuriser l'informatique embarquée combinant des mécanismes à différents niveaux de la pile protocolaire comme des environnements d'exécution. Nous décrivons nos protocoles sécurisés qui s'appuient sur une cryptographie efficace et intégrée au paradigme de communication dominant dans l'automobile et sur des modules de sécurité matériels fournissant un stockage sécurisé et un noyau de confiance. Nous décrivons aussi comment surveiller les flux d'information distribués dans le véhicule pour assurer une exécution conforme à la politique de sécurité des communications. L'instrumentation binaire du code, nécessaire pour l’industrialisation, est utilisée pour réaliser cette surveillance durant l’exécution (par data tainting) et entre ECUs (dans l’intergiciel). Nous évaluons la faisabilité de nos mécanismes pour sécuriser la communication sur le bus CAN aujourd'hui omniprésent dans les véhicules. Une preuve de concept montre aussi la faisabilité d'intégrer des mécanismes de sécurité dans des véhicules réels

Challenges and Open Questions of Machine Learning in Computer Security

This habilitation thesis presents advancements in machine learning for computer security, arising from problems in network intrusion detection and steganography. The thesis put an emphasis on explanation of traits shared by steganalysis, network intrusion detection, and other security domains, which makes these domains different from computer vision, speech recognition, and other fields where machine learning is typically studied. Then, the thesis presents methods developed to at least partially solve the identified problems with an overall goal to make machine learning based intrusion detection system viable. Most of them are general in the sense that they can be used outside intrusion detection and steganalysis on problems with similar constraints. A common feature of all methods is that they are generally simple, yet surprisingly effective. According to large-scale experiments they almost always improve the prior art, which is likely caused by being tailored to security problems and designed for large volumes of data. Specifically, the thesis addresses following problems: anomaly detection with low computational and memory complexity such that efficient processing of large data is possible; multiple-instance anomaly detection improving signal-to-noise ration by classifying larger group of samples; supervised classification of tree-structured data simplifying their encoding in neural networks; clustering of structured data; supervised training with the emphasis on the precision in top p% of returned data; and finally explanation of anomalies to help humans understand the nature of anomaly and speed-up their decision. Many algorithms and method presented in this thesis are deployed in the real intrusion detection system protecting millions of computers around the globe

XXV Congreso Argentino de Ciencias de la Computación - CACIC 2019: libro de actas

Trabajos presentados en el XXV Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de Río Cuarto los días 14 al 18 de octubre de 2019 organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y Facultad de Ciencias Exactas, Físico-Químicas y Naturales - Universidad Nacional de Río CuartoRed de Universidades con Carreras en Informátic

XXV Congreso Argentino de Ciencias de la Computación - CACIC 2019: libro de actas

Trabajos presentados en el XXV Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de Río Cuarto los días 14 al 18 de octubre de 2019 organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y Facultad de Ciencias Exactas, Físico-Químicas y Naturales - Universidad Nacional de Río CuartoRed de Universidades con Carreras en Informátic