Research on the Tracking Algorithm of Program Level Fine-grained Data based on Cloud Virtual Environment

Cloud now provides a wide range of services hosted by different providers from different domains. These services can be composed together dynamically to realize important tasks. In a composite service, information may flow from one service to subsequent services from different domains. Such information flow, if not properly controlled, may cause undesired leakage of critical data. Existing works on access control for web service do not consider the information flow problem in composite services. Existing information flow control (IFC) techniques is not flexible and cannot work with domain-specific information flow control policies. Existing works on access control for web service do not consider the information flow problem in composite services. Existing information flow control (IFC) techniques are not flexible and cannot work with domain-specific information flow control policies. In this paper, we define the WS-AIFC infrastructure for enforcing access and information flow control. The major goal of WS-AIFC is to provide a new IFC mechanism that can allow each domain to define their own IFC policies while WS-AIFC is capable of preventing undesired information leakage (IFC policy violation) among benign, semi-honest service domains. The main idea in WS-AIFC is to derive and record the dependency list for each data object. The system, upon receiving an access request to a critical data object, not only validates the conventional access control policy for the access, but also extracts the data and the corresponding domains in the dependency list and consults these domains to validate their IFC policies for the indirect access. In summary, WS-AIFC empowers individual domains to control how their information flows and achieves enhanced security for service based systems.

An information flow control model for C applications based on access control lists

An agent-based inter-application information flow control model

Concern about data leakage is holding back more widespread adoption of cloud computing by companies and public institutions alike. To address this, cloud tenants/applications are traditionally isolated in virtual machines or containers. But an emerging requirement is for cross-application sharing of data, for example, when cloud services form part of an IoT architecture. Information Flow Control (IFC) is ideally suited to achieving both isolation and data sharing as required. IFC enhances traditional Access Control by providing continuous, data-centric, cross-application, end-to-end control of data flows. However, large-scale data processing is a major requirement of cloud computing and is infeasible under standard IFC. We present a novel, enhanced IFC model that subsumes standard models. Our IFC model supports 'Big Data' processing, while retaining the simplicity of standard IFC and enabling more concise, accurate and maintainable expression of policy.

Information flow control (IFC) is useful in preventing information leakage during software execution.Our survey reveals that no IFC model is applied on the entire software development process.Applying an IFC model on the entire software development process offers the following features: (1) viewpoints of all stakeholders (i.e., customers and analysts) can be included and ( 2) the IFC model helps correcting statements that may leak information during every development phase.In addition that no IFC model is applied to the entire software development process, we failed to identify an IFC model that can reduce runtime overhead.According to the above description, we designed a new IFC model named PrcIFC (process IFC).PrcIFC is applied on the entire software development process.Moreover, PrcIFC is disabled after software testing to reduce runtime overhead.

The security of software-intensive systems is frequently attacked. High fines or loss in reputation are potential consequences of not maintaining confidentiality, which is an important security objective. Detecting confidentiality issues in early software designs enables cost-efficient fixes. A Data Flow Diagram (DFD) is a modeling notation, which focuses on essential, functional aspects of such early software designs. Existing confidentiality analyses on DFDs support either information flow control or access control, which are the most common confidentiality mechanisms. Combining both mechanisms can be beneficial but existing DFD analyses do not support this. This lack of expressiveness requires designers to switch modeling languages to consider both mechanisms, which can lead to inconsistencies. In this article, we present an extended DFD syntax that supports modeling both, information flow and access control, in the same language. This improves expressiveness compared to related work and avoids inconsistencies. We define the semantics of extended DFDs by clauses in first-order logic. A logic program made of these clauses enables the automated detection of confidentiality violations by querying it. We evaluate the expressiveness of the syntax in a case study. We attempt to model nine information flow cases and six access control cases. We successfully modeled fourteen out of these fifteen cases, which indicates good expressiveness. We evaluate the reusability of models when switching confidentiality mechanisms by comparing the cases that share the same system design, which are three pairs of cases. We successfully show improved reusability compared to the state of the art. We evaluated the accuracy of confidentiality analyses by executing them for the fourteen cases that we could model. We experienced good accuracy.

Mechanisms of neuroprogression and interventions to predict and arrest it

CDroid: practically implementation a formal-analyzed CIFC model on Android

A new generation of avionics system has three major technical characteristics of high resource sharing, data integration and software intensive. However, in the cooperative combat environment, which has the problem of potential sensitive information leakage and tamper when the combat aircraft communicate with each other. In this paper, we are based on the single node of information flow control model, combined with PCS, proposed a distributed information flow control model in MILS, constructed the PCS information flow control strategy, and together with other trusted component of information flow control strategy that form the multi-level information flow control policy framework, which design an information flow control mechanism of PCS and realized the distributed information flow control in MILS. After analysis and verification, the design of the distributed information flow security control method in MILS can effectively ensure the confidentiality and integrity of the information among the nodes.

Due to multi-tenancy, access control is a very important component in SaaS (Software as a Service), especially for controlling cross-tenant accesses. Due to the potential information flow among multiple tenants, information flow control should also be carefully addressed. Existing models for SaaS access control have some limitations, especially in information flow control. In this paper, we define a new SaaS-AIFC model to provide comprehensive and improved access and information flow control in SaaS. SaaS-AIFC incorporates two advanced features. First, SaaS-AIFC integrates the advanced role mapping technique to govern the cross-tenant accesses. Role mapping is very flexible and can be very efficient for SaaS with a large number of tenants. We integrate role mapping in SaaS by developing a detailed process for mapping establishment and retrieval during validation. Second, we propose a new IFC model in SaaS-AIFC, which tracks the dependency of data objects and uses the dependency information to achieve flexible information flow control. An architecture design for realizing the SaaS-AIFC model is also proposed.

Cloud computing is an emerging computing paradigm where computing resources are provided as services over Internet while residing in a large data center. Even though it enables us to dynamically provide servers with the ability to address a wide range of needs, this paradigm brings forth many new challenges for the data security and access control as users outsource their sensitive data to clouds, which are beyond the same trusted domain as data owners. A fundamental problem is the existence of insecure information flows due to the fact that a service provider can access multiple virtual machines in clouds. Sensitive information may be leaked to unauthorized customers and such critical information flows could raise conflict-of-interest issues in cloud computing. In this paper, we propose an approach to enforce the information flow policies at Infrastructure-as-a-Service (IaaS) layer in a cloud computing environment. Especially, we adopt Chinese Wall policies to address the problems of insecure information flow. We implement a proof-of-concept prototype system based on Eucalyptus open source packages to show the feasibility of our approach. This system facilitates the cloud management modules to resolve the conflict-of-interest issues for service providers in clouds.

Security concerns are widely seen as an obstacle to the adoption of cloud computing solutions. Information Flow Control (IFC) is a well understood Mandatory Access Control methodology. The earliest IFC models targeted security in a centralised environment, but decentralised forms of IFC have been designed and implemented, often within academic research projects. As a result, there is potential for decentralised IFC to achieve better cloud security than is available today. In this paper we describe the properties of cloud computing—Platform-as-a-Service clouds in particular—and review a range of IFC models and implementations to identify opportunities for using IFC within a cloud computing context. Since IFC security is linked to the data that it protects, both tenants and providers of cloud services can agree on security policy, in a manner that does not require them to understand and rely on the particulars of the cloud software stack in order to effect enforcement.

Role-based access control (RBAC) is useful in information security. It is a super set of discretionary access control (DAC) and mandatory access control (MAC). Since DAC and MAC are useful in information flow control (which protects privacy within an application), RBAC can certainly be used in that control. Our research reveals that different control granularity is needed in different cases when controlling information flows within an application. An information flow control model should thus simultaneously offer different levels of control granularity. We designed a multipleleveled RBAC model to offer multiple levels of control granularity, in which a level of RBAC controls a level of granularity. We called the model L n RBAC (n-leveled RBAC), which offer the following features: (1) it allows different control granularity in different cases, (2) it solves the covert channel problems caused by abnormal program stopping, (3) it adapts to dynamic object state change, (4) it controls method invocation through argument sensitivity (5) it allows purpose-oriented method invocation, (6) it controls write access precisely, and (7) it avoids Trojan horses. We implemented a prototype for L n RBAC and evaluated it. This paper presents L n RBACL.

Information flow control models can be applied widely.This paper discusses only the models preventing information leakage during program execution.In the prevention, an informat ion flow control model dynamically monitors statements that will cause information flows and ban statements that may cause leakage.We involved in the research of informat ion flow control for years and identified that sensitive informat ion may be leaked only when it is output.However, most existing models ignore informat ion flows induced by output statements.We thus designed a new model XIFC (X informat ion flow control) that especially emphasizes the monitoring of output statements.We also designed XIFC as a precise and low runtime overhead model.To achieve this purpose, we took a different viewpoint to re-examine the features offered by existing models and extracted a necessary feature set for the design.Our experiments show that XIFC bans every non-secure information flow and substantially reduces runtime overhead when comparing with our previous work.

The security issue has been a challenging concern for cloud computing because of the multitenant usage model. In cloud, each application normally runs on a dynamic coalition that is composed by multiple virtual machines (VMs) running on different virtualised service nodes, which the authors called logic virtual domain (LVD). Moreover, the owners of cloud applications, who are also the tenants of cloud, would specify some security policies to control the access to those resources that they have paid for. Therefore the owners of cloud infrastructures have to provide the tenants with the mechanism to correctly configure and enforce the access control policies on resources that are from multiple service nodes, to meet the security requirements from cloud applications. To address the above challenge, this study presents the design and implementation about a multilayer access control architecture for LVD, named CloudAC, aiming to provide isolation control, information flow control and resource-sharing control among multiple VMs on Xen virtualisation platforms in cloud computing environment. The theory and technology this research formed will provide reliable security guarantee for resource configuration and application deployment on LVDs.