Attributes Enhanced Role-Based Access Control Model

Abstract. Attribute-based access control (ABAC) and role-based access control (RBAC) are currently the two most popular access con-trol models. Yet, they both have known limitations and offer features complimentary to each other. Due to this fact, integration of RBAC and ABAC has recently emerged as an important area of research. In this paper, we propose an access control model that combines the two mod-els in a novel way in order to unify their benefits. Our approach provides a fine-grained access control mechanism that not only takes contextual information into account while making the access control decisions but is also suitable for applications where access to resources is controlled by exploiting contents of the resources in the policy

A Novel Approach to Fine-grained Content-based Access Control for Video Databases

ABSTRAC

Hybrid approach for XML access control (HyXAC)

While XML has been widely adopted for sharing and managing information over the Internet, the need for efficient XML access control naturally arise. Various access control models and mechanisms have been proposed in the research community, such as view-based approaches and preprocessing approaches. All categories of solutions have their inherent advantages and disadvantages. For instance, view based approach provides high performance in query evaluation, but suffers from the view maintenance issues. To remedy the problems, we propose a hybrid approach, namely HyXAC: Hybrid XML Access Control. HyXAC provides efficient access control and query processing by maximizing the utilization of available (but constrained) resources. HyXAC uses pre-processing approach as a baseline to process queries and define sub-views. It dynamically allocates the available resources (memory and secondary storage) to materialize sub-views to improve query performance. Dynamic and fine-grained view management is introduced to utilize cost-effectiveness analysis for optimal query performance. Fine-grained view management also allows sub-views to be shared across multiple roles to eliminate the redundancies in storage

Multi-Tier Diversified Service Architecture for Internet 3.0: The Next Generation Internet

The next generation Internet needs to support multiple diverse application contexts. In this paper, we present Internet 3.0, a diversified, multi-tier architecture for the next generation Internet. Unlike the current Internet, Internet 3.0 defines a new set of primitives that allows diverse applications to compose and optimize their specific contexts over resources belonging to multiple ownerships. The key design philosophy is to enable diversity through explicit representation, negotiation and enforcement of policies at the granularity of network infrastructure, compute resources, data and users. The basis of the Internet 3.0 architecture is a generalized three-tier object model. The bottom tier consists of a high-speed network infrastructure. The second tier consists of compute resources or hosts. The third tier consists of data and users. The “tiered” organization of the entities in the object model depicts the natural dependency relationship between these entities in a communication context. All communication contexts, including the current Internet, may be represented as special cases within this generalized three-tier object model. The key contribution of this paper is a formal architectural representation of the Internet 3.0 architecture over the key primitive of the “Object Abstraction” and a detailed discussion of the various design aspects of the architecture, including the design of the “Context Router-” the key architectural element that powers an evolutionary deployment plan for the clean slate design ideas of Internet 3.0

Security Analysis and Improvement Model for Web-based Applications

Today the web has become a major conduit for information. As the World Wide Web?s popularity continues to increase, information security on the web has become an increasing concern. Web information security is related to availability, confidentiality, and data integrity. According to the reports from http://www.securityfocus.com in May 2006, operating systems account for 9% vulnerability, web-based software systems account for 61% vulnerability, and other applications account for 30% vulnerability. In this dissertation, I present a security analysis model using the Markov Process Model. Risk analysis is conducted using fuzzy logic method and information entropy theory. In a web-based application system, security risk is most related to the current states in software systems and hardware systems, and independent of web application system states in the past. Therefore, the web-based applications can be approximately modeled by the Markov Process Model. The web-based applications can be conceptually expressed in the discrete states of (web_client_good; web_server_good, web_server_vulnerable, web_server_attacked, web_server_security_failed; database_server_good, database_server_vulnerable, database_server_attacked, database_server_security_failed) as state space in the Markov Chain. The vulnerable behavior and system response in the web-based applications are analyzed in this dissertation. The analyses focus on functional availability-related aspects: the probability of reaching a particular security failed state and the mean time to the security failure of a system. Vulnerability risk index is classified in three levels as an indicator of the level of security (low level, high level, and failed level). An illustrative application example is provided. As the second objective of this dissertation, I propose a security improvement model for the web-based applications using the GeoIP services in the formal methods. In the security improvement model, web access is authenticated in role-based access control using user logins, remote IP addresses, and physical locations as subject credentials to combine with the requested objects and privilege modes. Access control algorithms are developed for subjects, objects, and access privileges. A secure implementation architecture is presented. In summary, the dissertation has developed security analysis and improvement model for the web-based application. Future work will address Markov Process Model validation when security data collection becomes easy. Security improvement model will be evaluated in performance aspect

Content sensitivity based access control model for big data

Big data technologies have seen tremendous growth in recent years. They are being widely used in both industry and academia. In spite of such exponential growth, these technologies lack adequate measures to protect the data from misuse or abuse. Corporations that collect data from multiple sources are at risk of liabilities due to exposure of sensitive information. In the current implementation of Hadoop, only file level access control is feasible. Providing users, the ability to access data based on attributes in a dataset or based on their role is complicated due to the sheer volume and multiple formats (structured, unstructured and semi-structured) of data. In this dissertation an access control framework, which enforces access control policies dynamically based on the sensitivity of the data is proposed. This framework enforces access control policies by harnessing the data context, usage patterns and information sensitivity. Information sensitivity changes over time with the addition and removal of datasets, which can lead to modifications in the access control decisions and the proposed framework accommodates these changes. The proposed framework is automated to a large extent and requires minimal user intervention. The experimental results show that the proposed framework is capable of enforcing access control policies on non-multimedia datasets with minimal overhea

Data trust framework using blockchain and smart contracts

Lack of trust is the main barrier preventing more widespread data sharing. The lack of transparent and reliable infrastructure for data sharing prevents many data owners from sharing their data. Data trust is a paradigm that facilitates data sharing by forcing data controllers to be transparent about the process of sharing and reusing data. Blockchain technology has the potential to present the essential properties for creating a practical and secure data trust framework by transforming current auditing practices and automatic enforcement of smart contracts logic without relying on intermediaries to establish trust. Blockchain holds an enormous potential to remove the barriers of traditional centralized applications and propose a distributed and transparent administration by employing the involved parties to maintain consensus on the ledger. Furthermore, smart contracts are a programmable component that provides blockchain with more flexible and powerful capabilities. Recent advances in blockchain platforms toward smart contracts' development have revealed the possibility of implementing blockchain-based applications in various domains, such as health care, supply chain and digital identity. This dissertation investigates the blockchain's potential to present a framework for data trust. It starts with a comprehensive study of smart contracts as the main component of blockchain for developing decentralized data trust. Interrelated, three decentralized applications that address data sharing and access control problems in various fields, including healthcare data sharing, business process, and physical access control system, have been developed and examined. In addition, a general-purpose application based on an attribute-based access control model is proposed that can provide trusted auditability required for data sharing and access control systems and, ultimately, a data trust framework. Besides auditing, the system presents a transparency level that both access requesters (data users) and resource owners (data controllers) can benefit from. The proposed solutions have been validated through a use case of independent digital libraries. It also provides a detailed performance analysis of the system implementation. The performance results have been compared based on different consensus mechanisms and databases, indicating the system's high throughput and low latency. Finally, this dissertation presents an end-to-end data trust framework based on blockchain technology. The proposed framework promotes data trustworthiness by assessing input datasets, effectively managing access control, and presenting data provenance and activity monitoring. A trust assessment model that examines the trustworthiness of input data sets and calculates the trust value is presented. The number of transaction validators is defined adaptively with the trust value. This research provides solutions for both data owners and data users’ by ensuring the trustworthiness and quality of the data at origin and transparent and secure usage of the data at the end. A comprehensive experimental study indicates the presented system effectively handles a large number of transactions with low latency