139,776 research outputs found

    Fuzzy role-based access control

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    RBAC (Role-Based Access Control) is a widely used access control model, which reduces the maintenance cost of classical identity-based access control. However, despite the benefits of RBAC, there are environments in which RBAC can hardly be applied. We present FRBAC (Fuzzy Role-Based Access Control), a generalization of RBAC through fuzzy relations that extends the applicability of RBAC to environments where authorization-related information is vague. Moreover, FRBAC deals with environments where the actions that can be executed over the resources have a fractional meaning, as data lying in databases and risk-based access control. © 2011 Elsevier B.V. All rights reserved.Partial support by the Spanish MICINN (projects TSI2007-65406-C03-02, ARES- CONSOLIDER INGENIO 2010 CSD2007-00004) and Universitat Autonoma de Barcelona (PIF472-01-1/07) is acknowledged.Peer Reviewe

    Fuzzy role-based access control

    Get PDF
    RBAC (Role-Based Access Control) is a widely used access control model, which reduces the maintenance cost of classical identity-based access control. However, despite the benefits of RBAC, there are environments in which RBAC can hardly be applied. We present FRBAC (Fuzzy Role-Based Access Control), a generalization of RBAC through fuzzy relations that extends the applicability of RBAC to environments where authorization-related information is vague. Moreover, FRBAC deals with environments where the actions that can be executed over the resources have a fractional meaning, as data lying in databases and risk-based access control

    Internet of Thing Based Confidential Healthcare Data Storage, Access Control and Monitoring Using Blockchain Technique

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    Internet of Things plays a significant role in multiple sectors like agriculture, manufacturing and healthcare for collecting information to automation. The collected information is in different diversity and consists of confidential and non-confidential information. Secure handling of confidential data is a crucial task in cloud computing like storage, access control and monitoring. The blockchain based storage technique provides immutable data storage, efficient access control and dynamic monitoring to confidential data. Thus, the secure internet of things data storage, access control and monitoring using blockchain technique is proposed in this work. The patients health information that are in different formats are pruned by a decision tree algorithm and it classifies the confidential data and non-confidential data by the fuzzy rule classification technique. Depending on data owner's willing, the fuzzy rule is framed and the confidential and non-confidential data collected by internet of things sensors are classified. To provide confidentiality to confidential data, Attribute Based Encryption is applied to confidential data and stored in an off-chain mode of blockchain instead of entire data encryption and storage. The non-confidential data is stored in a plaintext form in cloud storage. When compared to support vector machine, K-nearest neighbor and Naive Bayes classification techniques, the proposed fuzzy rule based confidential data identification produces greater than 96 % of accuracy based on data owner willing and confidential data storage takes lesser than 20 % of storage space and processing time in an entire data storage. Additionally, the blockchain performances like throughput, network scalability and latency is optimized through minimal block size and transactions. Thus, our experimental results show that the proposed blockchain based internet of things data storage, access control and monitoring technique provides better confidentiality and access control to confidential data than the conventional cloud storage technique with lesser processing time

    Fuzzy-logic-based control, filtering, and fault detection for networked systems: A Survey

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    This paper is concerned with the overview of the recent progress in fuzzy-logic-based filtering, control, and fault detection problems. First, the network technologies are introduced, the networked control systems are categorized from the aspects of fieldbuses and industrial Ethernets, the necessity of utilizing the fuzzy logic is justified, and the network-induced phenomena are discussed. Then, the fuzzy logic control strategies are reviewed in great detail. Special attention is given to the thorough examination on the latest results for fuzzy PID control, fuzzy adaptive control, and fuzzy tracking control problems. Furthermore, recent advances on the fuzzy-logic-based filtering and fault detection problems are reviewed. Finally, conclusions are given and some possible future research directions are pointed out, for example, topics on two-dimensional networked systems, wireless networked control systems, Quality-of-Service (QoS) of networked systems, and fuzzy access control in open networked systems.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374039, 61473163, and 61374127, the Hujiang Foundation of China under Grants C14002 andD15009, the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

    Proposed L-Shape Pattern on UFS ACM For Risk Analysis

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    At this cloud age, there is tremendous growth in business, services, resources, and cloud technology. This growth comes with a risk of unsafe, unordered, and uncertainty due to unauthorized access and theft of confidential propriety data. Our objective is to model around Read, Write and Execute to resolve these unordered, unsafe, and uncertain issues. We will develop a L-Shape pattern model matching UFS ACM to minimize the accessibilities based on RIGHT & ROLE of the resources and maximize the quality of services for safety and high availability. The preventive, detective, corrective (PDC) services are the major roles for all levels of management to coordinate, control the multiple technologies and resources which are working simultaneously. It will be more ordered, accountable, and actionable on real-time access control mechanism for scalabilities, reliability, performance, and high availability of computational services. We have to make safer, certain, unified, and step-by-step normalization by applying this UFS ACM mechanism on UNIX operating system. This proposed research paper covers a wide range of areas covering optimization, normalization, Fuzzy Low, and Risk assessment

    Derivation of diagnostic models based on formalized process knowledge

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    © IFAC.Industrial systems are vulnerable to faults. Early and accurate detection and diagnosis in production systems can minimize down-time, increase the safety of the plant operation, and reduce manufacturing costs. Knowledge- and model-based approaches to automated fault detection and diagnosis have been demonstrated to be suitable for fault cause analysis within a broad range of industrial processes and research case studies. However, the implementation of these methods demands a complex and error-prone development phase, especially due to the extensive efforts required during the derivation of models and their respective validation. In an effort to reduce such modeling complexity, this paper presents a structured causal modeling approach to supporting the derivation of diagnostic models based on formalized process knowledge. The method described herein exploits the Formalized Process Description Guideline VDI/VDE 3682 to establish causal relations among key-process variables, develops an extension of the Signed Digraph model combined with the use of fuzzy set theory to allow more accurate causality descriptions, and proposes a representation of the resulting diagnostic model in CAEX/AutomationML targeting dynamic data access, portability, and seamless information exchange

    Ensuring patients privacy in a cryptographic-based-electronic health records using bio-cryptography

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    Several recent works have proposed and implemented cryptography as a means to preserve privacy and security of patients health data. Nevertheless, the weakest point of electronic health record (EHR) systems that relied on these cryptographic schemes is key management. Thus, this paper presents the development of privacy and security system for cryptography-based-EHR by taking advantage of the uniqueness of fingerprint and iris characteristic features to secure cryptographic keys in a bio-cryptography framework. The results of the system evaluation showed significant improvements in terms of time efficiency of this approach to cryptographic-based-EHR. Both the fuzzy vault and fuzzy commitment demonstrated false acceptance rate (FAR) of 0%, which reduces the likelihood of imposters gaining successful access to the keys protecting patients protected health information. This result also justifies the feasibility of implementing fuzzy key binding scheme in real applications, especially fuzzy vault which demonstrated a better performance during key reconstruction

    Information Flow Model for Commercial Security

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    Information flow in Discretionary Access Control (DAC) is a well-known difficult problem. This paper formalizes the fundamental concepts and establishes a theory of information flow security. A DAC system is information flow secure (IFS), if any data never flows into the hands of owner’s enemies (explicitly denial access list.
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