ScaRR: Scalable Runtime Remote Attestation for Complex Systems

The introduction of remote attestation (RA) schemes has allowed academia and industry to enhance the security of their systems. The commercial products currently available enable only the validation of static properties, such as applications fingerprint, and do not handle runtime properties, such as control-flow correctness. This limitation pushed researchers towards the identification of new approaches, called runtime RA. However, those mainly work on embedded devices, which share very few common features with complex systems, such as virtual machines in a cloud. A naive deployment of runtime RA schemes for embedded devices on complex systems faces scalability problems, such as the representation of complex control-flows or slow verification phase. In this work, we present ScaRR: the first Scalable Runtime Remote attestation schema for complex systems. Thanks to its novel control-flow model, ScaRR enables the deployment of runtime RA on any application regardless of its complexity, by also achieving good performance. We implemented ScaRR and tested it on the benchmark suite SPEC CPU 2017. We show that ScaRR can validate on average 2M control-flow events per second, definitely outperforming existing solutions.Comment: 14 page

Monitoring Data Integrity in Big Data Analytics Services

Enabled by advances in Cloud technologies, Big Data Analytics Services (BDAS) can improve many processes and identify extra information from previously untapped data sources. As our experience with BDAS and its benefits grows and technology for obtaining even more data improves, BDAS becomes ever more important for many different domains and for our daily lives. Most efforts in improving BDAS technologies have focused on scaling and efficiency issues. However, an equally important property is that of security, especially as we increasingly use public Cloud infrastructures instead of private ones. In this paper we present our approach for strengthening BDAS security by modifying the popular Spark infrastructure so as to monitor at run-time the integrity of data manipulated. In this way, we can ensure that the results obtained by the complex and resource-intensive computations performed on the Cloud are based on correct data and not data that have been tampered with or modified through faults in one of the many and complex subsystems of the overall system

A Secure Cloud-Based SCADA Application: the Use Case of a Water Supply Network

Cloud computing paradigm is gaining more and more momentum, to the extent that it is no more confined to its initial application domains, i.e. use by enterprises and businesses willing to lower costs or to increase computing capacity in a flexible manner. In particular, increasing interest is recently being paid to the huge potentials - in terms of benefits for the society at large - that might result from the adoption of cloud computing technology by critical infrastructure (CI) operators. This is of course putting special emphasis on the need for dependable and trustworthy security mechanisms in cloud technology based services, since a critical infrastructure is vital for essential functioning of a country. Incidental or deliberate damages to a CI have serious impacts on the economy, and possibly make essential services unavailable to the communities it serves. In this paper we present the proof-of concept of a cloud-based Water Supply Network Monitoring (WSNM) application, named RiskBuster (RB), that ensures the confidentiality and integrity of SCADA monitoring data collected from dam sensors and stored in the cloud by using the innovative Intel Software Guard eXtension (SGX) technology

Trusted execution: applications and verification

Useful security properties arise from sealing data to specific units of code. Modern processors featuring Intel’s TXT and AMD’s SVM achieve this by a process of measured and trusted execution. Only code which has the correct measurement can access the data, and this code runs in an environment trusted from observation and interference. We discuss the history of attempts to provide security for hardware platforms, and review the literature in the field. We propose some applications which would benefit from use of trusted execution, and discuss functionality enabled by trusted execution. We present in more detail a novel variation on Diffie-Hellman key exchange which removes some reliance on random number generation. We present a modelling language with primitives for trusted execution, along with its semantics. We characterise an attacker who has access to all the capabilities of the hardware. In order to achieve automatic analysis of systems using trusted execution without attempting to search a potentially infinite state space, we define transformations that reduce the number of times the attacker needs to use trusted execution to a pre-determined bound. Given reasonable assumptions we prove the soundness of the transformation: no secrecy attacks are lost by applying it. We then describe using the StatVerif extensions to ProVerif to model the bounded invocations of trusted execution. We show the analysis of realistic systems, for which we provide case studies

Protecting applications using trusted execution environments

While cloud computing has been broadly adopted, companies that deal with sensitive data are still reluctant to do so due to privacy concerns or legal restrictions. Vulnerabilities in complex cloud infrastructures, resource sharing among tenants, and malicious insiders pose a real threat to the confidentiality and integrity of sensitive customer data. In recent years trusted execution environments (TEEs), hardware-enforced isolated regions that can protect code and data from the rest of the system, have become available as part of commodity CPUs. However, designing applications for the execution within TEEs requires careful consideration of the elevated threats that come with running in a fully untrusted environment. Interaction with the environment should be minimised, but some cooperation with the untrusted host is required, e.g. for disk and network I/O, via a host interface. Implementing this interface while maintaining the security of sensitive application code and data is a fundamental challenge. This thesis addresses this challenge and discusses how TEEs can be leveraged to secure existing applications efficiently and effectively in untrusted environments. We explore this in the context of three systems that deal with the protection of TEE applications and their host interfaces: SGX-LKL is a library operating system that can run full unmodified applications within TEEs with a minimal general-purpose host interface. By providing broad system support inside the TEE, the reliance on the untrusted host can be reduced to a minimal set of low-level operations that cannot be performed inside the enclave. SGX-LKL provides transparent protection of the host interface and for both disk and network I/O. Glamdring is a framework for the semi-automated partitioning of TEE applications into an untrusted and a trusted compartment. Based on source-level annotations, it uses either dynamic or static code analysis to identify sensitive parts of an application. Taking into account the objectives of a small TCB size and low host interface complexity, it defines an application-specific host interface and generates partitioned application code. EnclaveDB is a secure database using Intel SGX based on a partitioned in-memory database engine. The core of EnclaveDB is its logging and recovery protocol for transaction durability. For this, it relies on the database log managed and persisted by the untrusted database server. EnclaveDB protects against advanced host interface attacks and ensures the confidentiality, integrity, and freshness of sensitive data.Open Acces

TREDIS – A Trusted Full-Fledged SGX-Enabled REDIS Solution

Currently, offloading storage and processing capacity to cloud servers is a growing trend among web-enabled services managing big datasets. This happens because high storage capacity and powerful processors are expensive, whilst cloud services provide cheaper, ongoing, elastic, and reliable solutions. The problem with this cloud-based out sourced solutions are that they are highly accessible through the Internet, which is good, but therefore can be considerably exposed to attacks, out of users’ control. By exploring subtle vulnerabilities present in cloud-enabled applications, management functions, op erating systems and hypervisors, an attacker may compromise the supported systems, thus compromising the privacy of sensitive user data hosted and managed in it. These attacks can be motivated by malicious purposes such as espionage, blackmail, identity theft, or harassment. A solution to this problem is processing data without exposing it to untrusted components, such as vulnerable OS components, which might be compromised by an attacker. In this thesis, we do a research on existent technologies capable of enabling appli cations to trusted environments, in order to adopt such approaches to our solution as a way to help deploy unmodified applications on top of Intel-SGX, with overheads com parable to applications designed to use this kind of technology, and also conducting an experimental evaluation to better understand how they impact our system. Thus, we present TREDIS - a Trusted Full-Fledged REDIS Key-Value Store solution, implemented as a full-fledged solution to be offered as a Trusted Cloud-enabled Platform as a Service, which includes the possibility to support a secure REDIS-cluster architecture supported by docker-virtualized services running in SGX-enabled instances, with operations run ning on always-encrypted in-memory datasets.A transição de suporte de aplicações com armazenamento e processamento em servidores cloud é uma tendência que tem vindo a aumentar, principalmente quando se precisam de gerir grandes conjuntos de dados. Comparativamente a soluções com licenciamento privado, as soluções de computação e armazenamento de dados em nuvens de serviços são capazes de oferecer opções mais baratas, de alta disponibilidade, elásticas e relativa mente confiáveis. Estas soluções fornecidas por terceiros são facilmente acessíveis através da Internet, sendo operadas em regime de outsourcing da sua operação, o que é bom, mas que por isso ficam consideravelmente expostos a ataques e fora do controle dos utiliza dores em relação às reais condições de confiabilidade, segurança e privacidade de dados. Ao explorar subtilmente vulnerabilidades presentes nas aplicações, funções de sistemas operativos (SOs), bibliotecas de virtualização de serviços de SOs ou hipervisores, um ata cante pode comprometer os sistemas e quebrar a privacidade de dados sensíveis. Estes ataques podem ser motivados por fins maliciosos como espionagem, chantagem, roubo de identidade ou assédio e podem ser desencadeados por intrusões (a partir de atacantes externos) ou por ações maliciosas ou incorretas de atacantes internos (podendo estes atuar com privilégios de administradores de sistemas). Uma solução para este problema passa por armazenar e processar a informação sem que existam exposições face a componentes não confiáveis. Nesta dissertação estudamos e avaliamos experimentalmente diversas tecnologias que permitem a execução de aplicações com isolamento em ambientes de execução confiá vel suportados em hardware Intel-SGX, de modo a perceber melhor como funcionam e como adaptá-las à nossa solução. Para isso, realizámos uma avaliação focada na utilização dessas tecnologias com virtualização em contentores isolados executando em hardware confiável, que usámos na concepção da nossa solução. Posto isto, apresentamos a nossa solução TREDIS - um sistema Key-Value Store confiável baseado em tecnologia REDIS, com garantias de integridade da execução e de privacidade de dados, concebida para ser usada como uma "Plataforma como Serviço"para gestão e armazenamento resiliente de dados na nuvem. Isto inclui a possibilidade de suportar uma arquitetura segura com garantias de resiliência semelhantes à arquitetura de replicação em cluster na solução original REDIS, mas em que os motores de execução de nós e a proteção de memória do cluster é baseado em contentores docker isolados e virtualizados em instâncias SGX, sendo os dados mantidos sempre cifrados em memória

Verbesserung von Cloud Sicherheit mithilfe von vertrauenswürdiger Ausführung

The increasing popularity of cloud computing also leads to a growing demand for security guarantees in cloud settings. Cloud customers want to be able to execute sensitive data processing in clouds only if a certain level of security can be guaranteed to them despite the unlimited power of the cloud provider over her infrastructure. However, security models for cloud computing mostly require the customers to trust the provider, its infrastructure and software stack completely. While this may be viable to some, it is by far not to all customers, and in turn reduces the speed of cloud adoption. In this thesis, the applicability of trusted execution technology to increase security in a cloud scenario is elaborated, as these technologies are recently becoming widespread available even in commodity hardware. However, applications should not naively be ported completely for usage of trusted execution technology as this would affect the resulting performance and security negatively. Instead they should be carefully crafted with specific characteristics of the used trusted execution technology in mind. Therefore, this thesis first comprises the discussion of various security goals of cloud-based applications and an overview of cloud security. Furthermore, it is investigated how the ARM TrustZone technology can be used to increase security of a cloud platform for generic applications. Next, securing standalone applications using trusted execution is described at the example of Intel SGX, focussing on relevant metrics that influence security as well as performance of such an application. Also based on Intel SGX, in this thesis a design of a trusted serverless cloud platform is proposed, reflecting the latest evolution of cloud-based applications.Die steigende Popularität von Cloud Computing führt zu immer mehr Nachfrage und auch strengeren Anforderungen an die Sicherheit in der Cloud. Nur wenn trotz der technischen Möglichkeiten eines Cloud Anbieters über seine eigene Infrastruktur ein entsprechendes Maß an Sicherheit garantiert werden kann, können Cloud Kunden sensible Daten einer Cloud Umgebung anvertrauen und diese dort verarbeiten. Das vorherrschende Paradigma bezüglich Sicherheit erfordert aktuell jedoch zumeist, dass der Kunde dem Cloud Provider, dessen Infrastruktur sowie den damit verbundenen Softwarekomponenten komplett vertraut. Während diese Vorgehensweise für manche Anwendungsfälle einen gangbaren Weg darstellen mag, ist dies bei Weitem nicht für alle Cloud Kunden eine Option, was nicht zuletzt auch die Annahme von Cloud Angeboten durch potentielle Kunden verlangsamt. In dieser Dissertation wird nun die Anwendbarkeit verschiedener Technologien für vertrauenswürdige Ausführung zur Verbesserung der Sicherheit in der Cloud untersucht, da solche Technologien in letzter Zeit auch in preiswerteren Hardwarekomponenten immer verbreiteter und verfügbarer werden. Es ist jedoch keine triviale Aufgabe existierende Anwendungen zur portieren, sodass diese von solch gearteten Technologien profitieren können, insbesondere wenn neben Sicherheit auch Effizienz und Performanz der Anwendung berücksichtigt werden soll. Stattdessen müssen Anwendungen sorgfältig unter verschiedenen spezifischen Gesichtspunkten der jeweiligen Technologie umgestaltet werden. Aus diesem Grund umfasst diese Dissertation zunächst eine Diskussion verschiedener Sicherheitsziele für Cloud-basierte Anwendungen und eine Übersicht über die Thematik "Cloud Sicherheit". Zunächst wird dann das Potential der ARM TrustZone Technologie zur Absicherung einer Cloud Plattform für generische Anwendungen untersucht. Anschließend wird beschrieben wie eigenständige und bestehende Anwendungen mittels vertrauenswürdiger Ausführung am Beispiel Intel SGX abgesichert werden können. Dabei wurde der Fokus auf relevante Metriken gesetzt, die die Sicherheit und Performanz einer solchen Anwendung beeinflussen. Zuletzt wird, ebenfalls basierend auf Intel SGX, eine vertrauenswürdige "Serverless" Cloud Plattform vorgestellt und damit auf aktuelle Trends für Cloud Plattformen eingegangen

Achieving trust-oriented data protection in the cloud environment

University of Technology, Sydney. Faculty of Engineering and Information Technology.Cloud computing has gained increasing acceptance in recent years. In privacy-conscious domains such as healthcare and banking, however, data security and privacy are the greatest obstacles to the widespread adoption of cloud computing technology. Despite enjoying the benefits brought by this innovative technology, users are concerned about losing the control of their own data in the outsourced environment. Encrypting data can resolve confidentiality and integrity challenges, but the key to mitigating users’ concerns and encouraging broader adoption of cloud computing is the establishment of a trustworthy relationship between cloud providers and users. In this dissertation, we investigate a novel trust-oriented data protection framework adapted to the cloud environment. By investigating cloud data security, privacy, and control related issues, we propose a novel data protection approach that combines active and passive protection mechanisms. The active protection is used to secure data in an independent and smart data cube that can survive even when the host is in danger. The passive protection covers the actions and mechanisms taken to monitor and audit data based on third party security services such as access control services and audit services. Furthermore, by incorporating full mobility and replica management with the active and passive mechanisms, the proposed framework can satisfy confidentiality, integrity, availability, scalability, intrusion-tolerance, authentication, authorization, auditability, and accountability, increasing users’ confidence in consuming cloud-based data services. In this work we begin by introducing cloud data storage characteristics and then analyse the reasons for issues of data security, privacy and control in cloud. On the basis of results of analysis, we identify desirable properties and objectives for protecting cloud data. In principle, cryptography-based and third party based approaches are insufficient to address users’ concerns and increase confidence in consuming cloud-based data services, because of possible intrusion attacks and direct tampering of data. Hence, we propose a novel way of securing data in an active data cube (ADCu) with smart and independent functionality. Each ADCu is a deployable data protection unit encapsulating sensitive data, networking, data manipulation, and security verification functions within a coherent data structure. A sealed and signed ADCu encloses dynamic information-flow tracking throughout the data cube that can precisely monitor the inner data and the derivatives. Any violations of policy or tampering with data would be compulsorily recorded and reported to bundled users via the mechanisms within the ADCu. This active and bundled architecture is designed to establish a trustworthy relationship between cloud and users. Subsequently, to establish a more comprehensive security environment cooperating with an active data-centric (ADC) framework, we propose a cloud-based privacy-aware role-based access control (CPRBAC) service and an active auditing service (AAS). These components in the entire data protection framework contribute to the passive security mechanisms. They provide access control management and audit work based on a consistent security environment. We also discuss and implement full mobility management and data replica management related to the ADCu, which are regarded as significant factors to satisfy data accountability, availability, and scalability. We conduct a set of practical experiments and security evaluation on a mini-private cloud platform. The outcome of this research demonstrates the efficiency, feasibility, dependability, and scalability of protecting outsourced data in cloud by using the trust-oriented protection framework. To that end, we introduce an application applying the components and mechanisms of the trust-oriented security framework to protecting eHealth data in cloud. The novelty of this work lies in protecting cloud data in an ADCu that is not highly reliant on strong encryption schemes and third-party protection schemes. By proposing innovative structures, concepts, algorithms, and services, the major contribution of this thesis is that it helps cloud providers to deliver trust actively to cloud users, and encourages broader adoption of cloud-based solutions for data storage services in sensitive areas

Chapter Securing the Home Energy Management Platform

Recently, many efforts have been done to chemically functionalize sensors surface to achieve selectivity towards diagnostics targets, such as DNA, RNA fragments and protein tumoural biomarkers, through the surface immobilization of the related specific receptor. Especially, some kind of sensors such as microcantilevers (gravimetric sensors) and one-dimensional photonics crystals (optical sensors) able to couple Bloch surface waves are very sensitive. Thus, any kind of surface modifications devoted to functionalize them has to be finely controlled in terms of mass and optical characteristics, such as refractive index, to minimize the perturbation, on the transduced signal, that can affect the response sensitivity towards the detected target species