‘Enhanced Encryption and Fine-Grained Authorization for Database Systems

The aim of this research is to enhance fine-grained authorization and encryption so that database systems are equipped with the controls necessary to help enterprises adhere to zero-trust security more effectively. For fine-grained authorization, this thesis has extended database systems with three new concepts: Row permissions, column masks and trusted contexts. Row permissions and column masks provide data-centric security so the security policy cannot be bypassed as with database views, for example. They also coexist in harmony with the rest of the database core tenets so that enterprises are not forced to compromise neither security nor database functionality. Trusted contexts provide applications in multitiered environments with a secure and controlled manner to propagate user identities to the database and therefore enable such applications to delegate the security policy to the database system where it is enforced more effectively. Trusted contexts also protect against application bypass so the application credentials cannot be abused to make database changes outside the scope of the application’s business logic. For encryption, this thesis has introduced a holistic database encryption solution to address the limitations of traditional database encryption methods. It too coexists in harmony with the rest of the database core tenets so that enterprises are not forced to choose between security and performance as with column encryption, for example. Lastly, row permissions, column masks, trusted contexts and holistic database encryption have all been implemented IBM DB2, where they are relied upon by thousands of organizations from around the world to protect critical data and adhere to zero-trust security more effectively

Securing Humanitarian Information Exchange: A Mediator-Wrapper Architecture

Reliable and secure information exchange, which is crucial for successful response to crisis by humanitarian organizations, requires the responding groups to swiftly organize themselves in new and dynamic ways. Within these resulting impromptu structures, planning, negotiation, and coordination poses significant problems, due to the heterogeneity of the technologies in place. A plethora of technical solutions have been proposed to solve information exchange issues. However, they thought of security as an ad-hoc, especially authentication, authorization, and access control. This paper proposes a conceptual platform, the Secured Humanitarian Information Sharing Architecture (SHISA), that enables heterogeneous humanitarian systems to exchange information while considering authentication, authorization, and access control. SHISA standardizes communication through the exchange of encrypted XML documents. It uses the Privilege Management Infrastructure (PMI) for authentication and authorization. The platform utilizes the mechanisms of indexing and impersonation to control data access so that humanitarian organizations\u27 users access only the information they need

Mitigating Insider Threat in Relational Database Systems

The dissertation concentrates on addressing the factors and capabilities that enable insiders to violate systems security. It focuses on modeling the accumulative knowledge that insiders get throughout legal accesses, and it concentrates on analyzing the dependencies and constraints among data items and represents them using graph-based methods. The dissertation proposes new types of Knowledge Graphs (KGs) to represent insiders\u27 knowledgebases. Furthermore, it introduces the Neural Dependency and Inference Graph (NDIG) and Constraints and Dependencies Graph (CDG) to demonstrate the dependencies and constraints among data items. The dissertation discusses in detail how insiders use knowledgebases and dependencies and constraints to get unauthorized knowledge. It suggests new approaches to predict and prevent the aforementioned threat. The proposed models use KGs, NDIG and CDG in analyzing the threat status, and leverage the effect of updates on the lifetimes of data items in insiders\u27 knowledgebases to prevent the threat without affecting the availability of data items. Furthermore, the dissertation uses the aforementioned idea in ordering the operations of concurrent tasks such that write operations that update risky data items in knowledgebases are executed before the risky data items can be used in unauthorized inferences. In addition to unauthorized knowledge, the dissertation discusses how insiders can make unauthorized modifications in sensitive data items. It introduces new approaches to build Modification Graphs that demonstrate the authorized and unauthorized data items which insiders are able to update. To prevent this threat, the dissertation provides two methods, which are hiding sensitive dependencies and denying risky write requests. In addition to traditional RDBMS, the dissertation investigates insider threat in cloud relational database systems (cloud RDMS). It discusses the vulnerabilities in the cloud computing structure that may enable insiders to launch attacks. To prevent such threats, the dissertation suggests three models and addresses the advantages and limitations of each one. To prove the correctness and the effectiveness of the proposed approaches, the dissertation uses well stated algorithms, theorems, proofs and simulations. The simulations have been executed according to various parameters that represent the different conditions and environments of executing tasks

Securing Databases from Probabilistic Inference

Databases can leak confidential information when users combine query results with probabilistic data dependencies and prior knowledge. Current research offers mechanisms that either handle a limited class of dependencies or lack tractable enforcement algorithms. We propose a foundation for Database Inference Control based on ProbLog, a probabilistic logic programming language. We leverage this foundation to develop Angerona, a provably secure enforcement mechanism that prevents information leakage in the presence of probabilistic dependencies. We then provide a tractable inference algorithm for a practically relevant fragment of ProbLog. We empirically evaluate Angerona's performance showing that it scales to relevant security-critical problems.Comment: A short version of this paper has been accepted at the 30th IEEE Computer Security Foundations Symposium (CSF 2017

Performance study of a COTS Distributed DBMS adapted for multilevel security

Multilevel secure database management system (MLS/DBMS) products no longer enjoy direct commercial-off-the-shelf (COTS) support. Meanwhile, existing users of these MLS/DBMS products continue to rely on them to satisfy their multilevel security requirements. This calls for a new approach to developing MLS/DBMS systems, one that relies on adapting the features of existing COTS database products rather than depending on the traditional custom design products to provide continuing MLS support. We advocate fragmentation as a good basis for implementing multilevel security in the new approach because it is well supported in some current COTS database management systems. We implemented a prototype that utilises the inherent advantages of the distribution scheme in distributed databases for controlling access to single-level fragments; this is achieved by augmenting the distribution module of the host distributed DBMS with MLS code such that the clearance of the user making a request is always compared to the classification of the node containing the fragments referenced; requests to unauthorised nodes are simply dropped. The prototype we implemented was used to instrument a series of experiments to determine the relative performance of the tuple, attribute, and element level fragmentation schemes. Our experiments measured the impact on the front-end and the network when various properties of each scheme, such as the number of tuples, attributes, security levels, and the page size, were varied for a Selection and Join query. We were particularly interested in the relationship between performance degradation and changes in the quantity of these properties. The performance of each scheme was measured in terms of its response time. The response times for the element level fragmentation scheme increased as the numbers of tuples, attributes, security levels, and the page size were increased, more significantly so than when the number of tuples and attributes were increased. The response times for the attribute level fragmentation scheme was the fastest, suggesting that the performance of the attribute level scheme is superior to the tuple and element level fragmentation schemes. In the context of assurance, this research has also shown that the distribution of fragments based on security level is a more natural approach to implementing security in MLS/DBMS systems, because a multilevel database is analogous to a distributed database based on security level. Overall, our study finds that the attribute level fragmentation scheme demonstrates better performance than the tuple and element level schemes. The response times (and hence the performance) of the element level fragmentation scheme exhibited the worst performance degradation compared to the tuple and attribute level schemes

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Access control models: Authorization mechanisms for database management systems

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Decentralized information flow control for databases

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 177-194).Privacy and integrity concerns have been mounting in recent years as sensitive data such as medical records, social network records, and corporate and government secrets are increasingly being stored in online systems. The rate of high-profile breaches has illustrated that current techniques are inadequate for protecting sensitive information. Many of these breaches involve databases that handle information for a multitude of individuals, but databases don't provide practical tools to protect those individuals from each other, so that task is relegated to the application. This dissertation describes a system that improves security in a principled way by extending the database system and the application platform to support information flow control. Information flow control has been gaining traction as a practical way to protect information in the contexts of programming languages and operating systems. Recent research advocates the decentralized model for information flow control (DIFC), since it provides the necessary expressiveness to protect data for many individuals with varied security concerns.However, despite the fact that most applications implicated in breaches rely on relational databases, there have been no prior comprehensive attempts to extend DIFC to a database system. This dissertation introduces IFDB, which is a database management system that supports DIFC with minimal overhead. IFDB pioneers the Query by Label model, which provides applications with a simple way to delineate constraints on the confidentiality and integrity of the data they obtain from the database. This dissertation also defines new abstractions for managing information flows in a database and proposes new ways to address covert channels. Finally, the IFDB implementation and case studies with real applications demonstrate that database support for DIFC improves security, is easy for developers to use, and has good performance.by David Andrew Schultz.Ph.D

A Study of Access Control for Electronic Health Records

The expansion between Information Technology and Healthcare has created many new options for both disciplines, as well as challenges. One of these topics is the Electronic Health Record (EHR) and the push for a universal record. A challenge for this topic is access control: how to keep patient’s personal health information secure, but at the same time accessible to all fields of healthcare and accomplish this within the federal privacy laws made by our government. This study focuses on the idea of a single EHR containing all the different medical information for all the areas of healthcare for a patient. This single EHR would be stored in a database and its use secured though the use of access control using a hierarchy of user groups, which would be divided into different roles to assign access privileges. This access control method would be implemented by possibly using mechanisms such as Bell-LaPadulla Model, The Strawman Design, Public/Private Key algorithms, or other methods. The first goal would be to create this structure for a single entity (e.g., One Hospital, Clinic, or Doctor’s office) and then progress to a distributed model where multiple entities can store and share information