91 research outputs found

    Infrastructural Security for Virtualized Grid Computing

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    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

    Music, Padlocks and the Commons

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    Depuis l’avĂšnement des formats de compression numĂ©rique et des services d’échange point Ă  point (Peer-to-Peer) comme Napster, l’industrie du disque est en Ă©moi. Plus fondamentalement, il y a lieu de se questionner sur ce qui apparaĂźt comme une crise d’efficacitĂ© du droit d’auteur. Si les copistes semblent avoir pris de court de puissants intĂ©rĂȘts, les contre-mesures ne sauraient tarder Ă  venir. L’apparition de protections techniques ­ Trusted Systems ­ prĂ©sage une Ăšre de contrĂŽle total par les titulaires de droits. L’«hyper efficacité» bouleversera le rapport Ă  l’Ɠuvre, entraĂźnant du mĂȘme souffle un dĂ©sĂ©quilibre dans les dimensions privĂ©e et publique du droit d’auteur.Since the advent of the digital compression formats and Peer-to-Peer transaction services like Napster, the recording industry is in a state of disarray. Fundamentally, there is reason to reflect on what appears to be a copyright efficacy crisis. While the copyists seemed to have gained an upper hand against some powerful interests, countermeasures are in the wake. The foreseeable implementation of secured formats, so-called Trusted Systems, portends an era of total control by the titleholders. ‘Super efficacy’ will radically change in relation to the work, compromising the balance struck between the private and public dimensions of copyright law

    Distributed detection of anomalous internet sessions

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    Financial service providers are moving many services online reducing their costs and facilitating customersÂż interaction. Unfortunately criminals have quickly found several ways to avoid most security measures applied to browsers and banking sites. The use of highly dangerous malware has become the most significant threat and traditional signature-detection methods are nowadays easily circumvented due to the amount of new samples and the use of sophisticated evasion techniques. Antivirus vendors and malware experts are pushed to seek for new methodologies to improve the identification and understanding of malicious applications behavior and their targets. Financial institutions are now playing an important role by deploying their own detection tools against malware that specifically affect their customers. However, most detection approaches tend to base on sequence of bytes in order to create new signatures. This thesis approach is based on new sources of information: the web logs generated from each banking session, the normal browser execution and customers mobile phone behavior. The thesis can be divided in four parts: The first part involves the introduction of the thesis along with the presentation of the problems and the methodology used to perform the experimentation. The second part describes our contributions to the research, which are based in two areas: *Server side: Weblogs analysis. We first focus on the real time detection of anomalies through the analysis of web logs and the challenges introduced due to the amount of information generated daily. We propose different techniques to detect multiple threats by deploying per user and global models in a graph based environment that will allow increase performance of a set of highly related data. *Customer side: Browser analysis. We deal with the detection of malicious behaviors from the other side of a banking session: the browser. Malware samples must interact with the browser in order to retrieve or add information. Such relation interferes with the normal behavior of the browser. We propose to develop models capable of detecting unusual patterns of function calls in order to detect if a given sample is targeting an specific financial entity. In the third part, we propose to adapt our approaches to mobile phones and Critical Infrastructures environments. The latest online banking attack techniques circumvent protection schemes such password verification systems send via SMS. Man in the Mobile attacks are capable of compromising mobile devices and gaining access to SMS traffic. Once the Transaction Authentication Number is obtained, criminals are free to make fraudulent transfers. We propose to model the behavior of the applications related messaging services to automatically detect suspicious actions. Real time detection of unwanted SMS forwarding can improve the effectiveness of second channel authentication and build on detection techniques applied to browsers and Web servers. Finally, we describe possible adaptations of our techniques to another area outside the scope of online banking: critical infrastructures, an environment with similar features since the applications involved can also be profiled. Just as financial entities, critical infrastructures are experiencing an increase in the number of cyber attacks, but the sophistication of the malware samples utilized forces to new detection approaches. The aim of the last proposal is to demonstrate the validity of out approach in different scenarios. Conclusions. Finally, we conclude with a summary of our findings and the directions for future work

    Investigating Advances in the Acquisition of Secure Systems Based on Open Architecture, Open Source Software, and Software Product Lines

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    Naval Postgraduate School Acquisition Research Progra

    Analysis avoidance techniques of malicious software

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    Anti Virus (AV) software generally employs signature matching and heuristics to detect the presence of malicious software (malware). The generation of signatures and determination of heuristics is dependent upon an AV analyst having successfully determined the nature of the malware, not only for recognition purposes, but also for the determination of infected files and startup mechanisms that need to be removed as part of the disinfection process. If a specimen of malware has not been previously extensively analyzed, it is unlikely to be detected by AV software. In addition, malware is becoming increasingly profit driven and more likely to incorporate stealth and deception techniques to avoid detection and analysis to remain on infected systems for a myriad of nefarious purposes. Malware extends beyond the commonly thought of virus or worm, to customized malware that has been developed for specific and targeted miscreant purposes. Such customized malware is highly unlikely to be detected by AV software because it will not have been previously analyzed and a signature will not exist. Analysis in such a case will have to be conducted by a digital forensics analyst to determine the functionality of the malware. Malware can employ a plethora of techniques to hinder the analysis process conducted by AV and digital forensics analysts. The purpose of this research has been to answer three research questions directly related to the employment of these techniques as: 1. What techniques can malware use to avoid being analyzed? 2. How can the use of these techniques be detected? 3. How can the use of these techniques be mitigated

    Securely Handling Inter-Application Connection Credentials

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    The utilization of application-to-application (A2A) credentials within interpretive language scripts and application code has long been a security risk. The quandaries being how to protect and secure the credentials handled in the main body of code and avoid exploitation from rogue programmers, system administrators and other users with authorized high levels of privilege. Researchers report that A2A credentials cannot be protected and that there is no way to reduce the risk of the inevitable successful attack and subsequent exploit. Therefore, research efforts to date have primarily been focused on mitigating the impact of the attack rather than finding ways to reduce the attack surface. The work contained herein successfully addresses this serious cross-cutting concern and proves that it is in fact possible to significantly reduce the risk of attack. This reduction of risk was accomplished through implementing a method of credential obfuscation which applied advice with concerns utilizing a composition filter. The filter modified messages containing the credentials as they were sent from the interpretive language script to the remote data store. The modification extracted credentials from a secure password vault and inserted them into the message being sent to the remote data store. This modification moved the handling of the credentials from the main body of code to a secure library and out of the reach of attackers with authorized high levels of privilege. The relocation of the credential handling code lines significantly reduced the attack surface and the overall risk of attack

    On the malware detection problem : challenges and novel approaches

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    Orientador: AndrĂ© Ricardo Abed GrĂ©gioCoorientador: Paulo LĂ­cio de GeusTese (doutorado) - Universidade Federal do ParanĂĄ, Setor de CiĂȘncias Exatas, Programa de PĂłs-Graduação em InformĂĄtica. Defesa : Curitiba,Inclui referĂȘnciasÁrea de concentração: CiĂȘncia da ComputaçãoResumo: Software Malicioso (malware) Ă© uma das maiores ameaças aos sistemas computacionais atuais, causando danos Ă  imagem de indivĂ­duos e corporaçÔes, portanto requerendo o desenvolvimento de soluçÔes de detecção para prevenir que exemplares de malware causem danos e para permitir o uso seguro dos sistemas. Diversas iniciativas e soluçÔes foram propostas ao longo do tempo para detectar exemplares de malware, de Anti-VĂ­rus (AVs) a sandboxes, mas a detecção de malware de forma efetiva e eficiente ainda se mantĂ©m como um problema em aberto. Portanto, neste trabalho, me proponho a investigar alguns desafios, falĂĄcias e consequĂȘncias das pesquisas em detecção de malware de modo a contribuir para o aumento da capacidade de detecção das soluçÔes de segurança. Mais especificamente, proponho uma nova abordagem para o desenvolvimento de experimentos com malware de modo prĂĄtico mas ainda cientĂ­fico e utilizo-me desta abordagem para investigar quatro questĂ”es relacionadas a pesquisa em detecção de malware: (i) a necessidade de se entender o contexto das infecçÔes para permitir a detecção de ameaças em diferentes cenĂĄrios; (ii) a necessidade de se desenvolver melhores mĂ©tricas para a avaliação de soluçÔes antivĂ­rus; (iii) a viabilidade de soluçÔes com colaboração entre hardware e software para a detecção de malware de forma mais eficiente; (iv) a necessidade de predizer a ocorrĂȘncia de novas ameaças de modo a permitir a resposta Ă  incidentes de segurança de forma mais rĂĄpida.Abstract: Malware is a major threat to most current computer systems, causing image damages and financial losses to individuals and corporations, thus requiring the development of detection solutions to prevent malware to cause harm and allow safe computers usage. Many initiatives and solutions to detect malware have been proposed over time, from AntiViruses (AVs) to sandboxes, but effective and efficient malware detection remains as a still open problem. Therefore, in this work, I propose taking a look on some malware detection challenges, pitfalls and consequences to contribute towards increasing malware detection system's capabilities. More specifically, I propose a new approach to tackle malware research experiments in a practical but still scientific manner and leverage this approach to investigate four issues: (i) the need for understanding context to allow proper detection of localized threats; (ii) the need for developing better metrics for AV solutions evaluation; (iii) the feasibility of leveraging hardware-software collaboration for efficient AV implementation; and (iv) the need for predicting future threats to allow faster incident responses

    Mitigating security and privacy threats from untrusted application components on Android

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    Aufgrund von Androids datenzentrierter und Open-Source Natur sowie von fehlerhaften/bösartigen Apps durch das lockere Marktzulassungsverfahren, ist die PrivatsphĂ€re von Benutzern besonders gefĂ€hrdet. Diese Dissertation prĂ€sentiert eine Reihe von Forschungsarbeiten, die die Bedrohung der Sicherheit/PrivatsphĂ€re durch nicht vertrauenswĂŒrdige Appkomponenten mindern. Die erste Arbeit stellt eine Compiler-basierte Kompartmentalisierungslösung vor, die Privilegientrennung nutzt, um eine starke Barriere zwischen der Host-App und Bibliothekskomponenten zu etablieren, und somit sensible Daten vor der Kompromittierung durch neugierige/bösartige Werbe-Bibliotheken schĂŒtzt. FĂŒr fehleranfĂ€llige Bibliotheken von Drittanbietern implementieren wir in der zweiten Arbeit ein auf API-KompatibilitĂ€t basierendes Bibliothek-Update-Framework, das veraltete Bibliotheken durch Drop-Ins aktualisiert, um das durch Bibliotheken verursachte Zeitfenster der Verwundbarkeit zu minimieren. Die neueste Arbeit untersucht die missbrĂ€uchliche Nutzung von privilegierten Accessibility(a11y)-Funktionen in bösartigen Apps. Wir zeigen ein datenschutzfreundliches a11y-Framework, das die a11y-Logik wie eine Pipeline behandelt, die aus mehreren Modulen besteht, die in verschiedenen Sandboxen laufen. Weiterhin erzwingen wir eine Flusskontrolle ĂŒber die Kommunikation zwischen den Modulen, wodurch die AngriffsflĂ€che fĂŒr den Missbrauch von a11y-APIs verringert wird, wĂ€hrend die Vorteile von a11y erhalten bleiben.While Android’s data-intensive and open-source nature, combined with its less-than-strict market approval process, has allowed the installation of flawed and even malicious apps, its coarse-grained security model and update bottleneck in the app ecosystem make the platform’s privacy and security situation more worrying. This dissertation introduces a line of works that mitigate privacy and security threats from untrusted app components. The first work presents a compiler-based library compartmentalization solution that utilizes privilege separation to establish a strong trustworthy boundary between the host app and untrusted lib components, thus protecting sensitive user data from being compromised by curious or malicious ad libraries. While for vulnerable third-party libraries, we then build the second work that implements an API-compatibility-based library update framework using drop-in replacements of outdated libraries to minimize the open vulnerability window caused by libraries and we perform multiple dynamic tests and case studies to investigate its feasibility. Our latest work focuses on the misusing of powerful accessibility (a11y) features in untrusted apps. We present a privacy-enhanced a11y framework that treats the a11y logic as a pipeline composed of multiple modules running in different sandboxes. We further enforce flow control over the communication between modules, thus reducing the attack surface from abusing a11y APIs while preserving the a11y benefits
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