Scalable And Secure Provenance Querying For Scientific Workflows And Its Application In Autism Study

In the era of big data, scientific workflows have become essential to automate scientific experiments and guarantee repeatability. As both data and workflow increase in their scale, requirements for having a data lineage management system commensurate with the complexity of the workflow also become necessary, calling for new scalable storage, query, and analytics infrastructure. This system that manages and preserves the derivation history and morphosis of data, known as provenance system, is essential for maintaining quality and trustworthiness of data products and ensuring reproducibility of scientific discoveries. With a flurry of research and increased adoption of scientific workflows in processing sensitive data, i.e., health and medication domain, securing information flow and instrumenting access privileges in the system have become a fundamental precursor to deploying large-scale scientific workflows. That has become more important now since today team of scientists around the world can collaborate on experiments using globally distributed sensitive data sources. Hence, it has become imperative to augment scientific workflow systems as well as the underlying provenance management systems with data security protocols. Provenance systems, void of data security protocol, are susceptible to vulnerability. In this dissertation research, we delineate how scientific workflows can improve therapeutic practices in autism spectrum disorders. The data-intensive computation inherent in these workflows and sensitive nature of the data, necessitate support for scalable, parallel and robust provenance queries and secured view of data. With that in perspective, we propose $OPQL^{Pig}$, a parallel, robust, reliable and scalable provenance query language and introduce the concept of access privilege inheritance in the provenance systems. We characterize desirable properties of role-based access control protocol in scientific workflows and demonstrate how the qualities are integrated into the workflow provenance systems as well. Finally, we describe how these concepts fit within the DATAVIEW workflow management system

Modelling of user requirements and behaviors in computational grids

In traditional distributed computing systems a few user types are found having ratherPeer ReviewedPostprint (published version

Vérification et validation de politiques de contrôle d'accès dans le domaine médical

Dans le domaine médical, la numérisation des documents et l’utilisation des dossiers patient électroniques (DPE, ou en anglais EHR pour Electronic Health Record) offrent de nombreux avantages, tels que la facilité de recherche et de transmission de ces données. Les systèmes informatiques doivent reprendre ainsi progressivement le rôle traditionnellement tenu par les archivistes, rôle qui comprenait notamment la gestion des accès à ces données sensibles. Ces derniers doivent en effet être rigoureusement contrôlés pour tenir compte des souhaits de confidentialité des patients, des règles des établissements et de la législation en vigueur. SGAC, ou Solution de Gestion Automatisée du Consentement, a pour but de fournir une solution dans laquelle l’accès aux données du patient serait non seulement basée sur les règles mises en place par le patient lui-même mais aussi sur le règlement de l’établissement et sur la législation. Cependant, cette liberté octroyée au patient est source de divers problèmes : conflits, masquage des données nécessaires aux soins ou encore tout simplement erreurs de saisie. Pour effectuer ces vérifications, les méthodes formelles fournissent des moyens fiables de vérification de propriétés tels que les preuves ou la vérification de modèles. Cette thèse propose des méthodes de vérification adaptées à SGAC pour le patient : elle introduit le modèle formel de SGAC, des méthodes de vérifications de propriétés. Afin de mener ces vérifications de manière automatisée, SGAC est modélisé en B et Alloy ; ces différentes modélisations donnent accès aux outils Alloy et ProB, et ainsi à la vérification automatisée de propriétés via la vérification de modèles ou model checking.Abstract : In healthcare, data digitization and the use of the Electronic Health Records (EHR) offer several benefits, such as the reduction of the space occupied by data, or the ease of data search or data exchanges. IT systems must gradually take up the archivist’s role by managing the accesses over sensitive data, which have to be compliant with patient wishes, hospital rules, as well as laws and regulations. SGAC, or Solution de Gestion Automatisée du Consentement (Automated Consent Management Solution), aims to provide a solution in which access to patient data would be based on patient rules, hospital rules and laws. However, the freedom granted to the patient can cause several problems : conflicts, concealment of crucial data needed to treat the patient adequately, and data-capture errors. Therefore, verification and validation of policies are essential : formal methods provide reliable ways, such as proofs or model checking, to conduct verifications of properties. This thesis provides verification methods applied on SGAC for the patient : it introduces the formal model of SGAC, methods to verify properties such as data access resolution, hidden data detection or redundant rule identification. Modeling of SGAC in B and Alloy provides access to the tools Alloy and ProB, and thus, automated property verification through model checking

Securing the software-defined networking control plane by using control and data dependency techniques

Software-defined networking (SDN) fundamentally changes how network and security practitioners design, implement, and manage their networks. SDN decouples the decision-making about traffic forwarding (i.e., the control plane) from the traffic being forwarded (i.e., the data plane). SDN also allows for network applications, or apps, to programmatically control network forwarding behavior and policy through a logically centralized control plane orchestrated by a set of SDN controllers. As a result of logical centralization, SDN controllers act as network operating systems in the coordination of shared data plane resources and comprehensive security policy implementation. SDN can support network security through the provision of security services and the assurances of policy enforcement. However, SDN’s programmability means that a network’s security considerations are different from those of traditional networks. For instance, an adversary who manipulates the programmable control plane can leverage significant control over the data plane’s behavior. In this dissertation, we demonstrate that the security posture of SDN can be enhanced using control and data dependency techniques that track information flow and enable understanding of application composability, control and data plane decoupling, and control plane insight. We support that statement through investigation of the various ways in which an attacker can use control flow and data flow dependencies to influence the SDN control plane under different threat models. We systematically explore and evaluate the SDN security posture through a combination of runtime, pre-runtime, and post-runtime contributions in both attack development and defense designs. We begin with the development a conceptual accountability framework for SDN. We analyze the extent to which various entities within SDN are accountable to each other, what they are accountable for, mechanisms for assurance about accountability, standards by which accountability is judged, and the consequences of breaching accountability. We discover significant research gaps in SDN’s accountability that impact SDN’s security posture. In particular, the results of applying the accountability framework showed that more control plane attribution is necessary at different layers of abstraction, and that insight motivated the remaining work in this dissertation. Next, we explore the influence of apps in the SDN control plane’s secure operation. We find that existing access control protections that limit what apps can do, such as role-based access controls, prove to be insufficient for preventing malicious apps from damaging control plane operations. The reason is SDN’s reliance on shared network state. We analyze SDN’s shared state model to discover that benign apps can be tricked into acting as “confused deputies”; malicious apps can poison the state used by benign apps, and that leads the benign apps to make decisions that negatively affect the network. That violates an implicit (but unenforced) integrity policy that governs the network’s security. Because of the strong interdependencies among apps that result from SDN’s shared state model, we show that apps can be easily co-opted as “gadgets,” and that allows an attacker who minimally controls one app to make changes to the network state beyond his or her originally granted permissions. We use a data provenance approach to track the lineage of the network state objects by assigning attribution to the set of processes and agents responsible for each control plane object. We design the ProvSDN tool to track API requests from apps as they access the shared network state’s objects, and to check requests against a predefined integrity policy to ensure that low-integrity apps cannot poison high-integrity apps. ProvSDN acts as both a reference monitor and an information flow control enforcement mechanism. Motivated by the strong inter-app dependencies, we investigate whether implicit data plane dependencies affect the control plane’s secure operation too. We find that data plane hosts typically have an outsized effect on the generation of the network state in reactive-based control plane designs. We also find that SDN’s event-based design, and the apps that subscribe to events, can induce dependencies that originate in the data plane and that eventually change forwarding behaviors. That combination gives attackers that are residing on data plane hosts significant opportunities to influence control plane decisions without having to compromise the SDN controller or apps. We design the EventScope tool to automatically identify where such vulnerabilities occur. EventScope clusters apps’ event usage to decide in which cases unhandled events should be handled, statically analyzes controller and app code to understand how events affect control plane execution, and identifies valid control flow paths in which a data plane attacker can reach vulnerable code to cause unintended data plane changes. We use EventScope to discover 14 new vulnerabilities, and we develop exploits that show how such vulnerabilities could allow an attacker to bypass an intended network (i.e., data plane) access control policy. This research direction is critical for SDN security evaluation because such vulnerabilities could be induced by host-based malware campaigns. Finally, although there are classes of vulnerabilities that can be removed prior to deployment, it is inevitable that other classes of attacks will occur that cannot be accounted for ahead of time. In those cases, a network or security practitioner would need to have the right amount of after-the-fact insight to diagnose the root causes of such attacks without being inundated with too much informa- tion. Challenges remain in 1) the modeling of apps and objects, which can lead to overestimation or underestimation of causal dependencies; and 2) the omission of a data plane model that causally links control and data plane activities. We design the PicoSDN tool to mitigate causal dependency modeling challenges, to account for a data plane model through the use of the data plane topology to link activities in the provenance graph, and to account for network semantics to appropriately query and summarize the control plane’s history. We show how prior work can hinder investigations and analysis in SDN-based attacks and demonstrate how PicoSDN can track SDN control plane attacks.Ope

Towards Secure and Leak-Free Workflows Using Microservice Isolation

Data leaks and breaches are on the rise. They result in huge losses of money for businesses like the movie industry, as well as a loss of user privacy for businesses dealing with user data like the pharmaceutical industry. Preventing data exposures is challenging, because the causes for such events are various, ranging from hacking to misconfigured databases. Alongside the surge in data exposures, the recent rise of microservices as a paradigm brings the need to not only secure traffic at the border of the network, but also internally, pressing the adoption of new security models such as zero-trust to secure business processes. Business processes can be modeled as workflows, where the owner of the data at risk interacts with contractors to realize a sequence of tasks on this data. In this paper, we show how those workflows can be enforced while preventing data exposure. Following the principles of zero-trust, we develop an infrastructure using the isolation provided by a microservice architecture, to enforce owner policy. We show that our infrastructure is resilient to the set of attacks considered in our security model. We implement a simple, yet realistic, workflow with our infrastructure in a publicly available proof of concept. We then verify that the specified policy is correctly enforced by testing the deployment for policy violations, and estimate the overhead cost of authorization

Access Control Administration with Adjustable Decentralization

Access control is a key function of enterprises that preserve and propagate massive data. Access control enforcement and administration are two major components of the system. On one hand, enterprises are responsible for data security; thus, consistent and reliable access control enforcement is necessary although the data may be distributed. On the other hand, data often belongs to several organizational units with various access control policies and many users; therefore, decentralized administration is needed to accommodate diverse access control needs and to avoid the central bottleneck. Yet, the required degree of decentralization varies within different organizations: some organizations may require a powerful administrator in the system; whereas, some others may prefer a self-governing setting in which no central administrator exists, but users fully manage their own data. Hence, a single system with adjustable decentralization will be useful for supporting various (de)centralized models within the spectrum of access control administration. Giving individual users the ability to delegate or grant privileges is a means of decentralizing access control administration. Revocation of arbitrary privileges is a means of retaining control over data. To provide flexible administration, the ability to delegate a specific privilege and the ability to revoke it should be held independently of each other and independently of the privilege itself. Moreover, supporting arbitrary user and data hierarchies, fine-grained access control, and protection of both data (end objects) and metadata (access control data) with a single uniform model will provide the most widely deployable access control system. Conflict resolution is a major aspect of access control administration in systems. Resolving access conflicts when deriving effective privileges from explicit ones is a challenging problem in the presence of both positive and negative privileges, sophisticated data hierarchies, and diversity of conflict resolution strategies. This thesis presents a uniform access control administration model with adjustable decentralization, to protect both data and metadata. There are several contributions in this work. First, we present a novel mechanism to constrain access control administration for each object type at object creation time, as a means of adjusting the degree of decentralization for the object when the system is configured. Second, by controlling the access control metadata with the same mechanism that controls the users’ data, privileges can be granted and revoked to the extent that these actions conform to the corporation’s access control policy. Thus, this model supports a whole spectrum of access control administration, in which each model is characterized as a network of access control states, similar to a finite state automaton. The model depends on a hierarchy of access banks of authorizations which is supported by a formal semantics. Within this framework, we also introduce the self-governance property in the context of access control, and show how the model facilitates it. In particular, using this model, we introduce a conflict-free and decentralized access control administration model in which all users are able to retain complete control over their own data while they are also able to delegate any subset of their privileges to other users or user groups. We also introduce two measures to compare any two access control models in terms of the degrees of decentralization and interpretation. Finally, as the conflict resolution component of access control models, we incorporate a unified algorithm to resolve access conflicts by simultaneously supporting several combined strategies

AuthN-AuthZ: Integrated, User-Friendly and Privacy-Preserving Authentication and Authorization

In this paper, we propose a novel, privacy-preserving, and integrated authentication and authorization scheme (dubbed as AuthN-AuthZ). The proposed scheme can address both the usability and privacy issues often posed by authentication through use of privacy-preserving Biometric-Capsule-based authentication. Each Biometric-Capsule encapsulates a user's biometric template as well as their role within a hierarchical Role-based Access Control model. As a result, AuthN-AuthZ provides novel efficiency by performing both authentication and authorization simultaneously in a single operation. To the best of our knowledge, our scheme's integrated AuthN-AuthZ operation is the first of its kind. The proposed scheme is flexible in design and allows for the secure use of robust deep learning techniques, such as the recently proposed and current state-of-the-art facial feature representation method, ArcFace. We conduct extensive experiments to demonstrate the robust performance of the proposed scheme and its AuthN-AuthZ operation