1,943 research outputs found

    A HYBRIDIZED ENCRYPTION SCHEME BASED ON ELLIPTIC CURVE CRYPTOGRAPHY FOR SECURING DATA IN SMART HEALTHCARE

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    Recent developments in smart healthcare have brought us a great deal of convenience. Connecting common objects to the Internet is made possible by the Internet of Things (IoT). These connected gadgets have sensors and actuators for data collection and transfer. However, if users' private health information is compromised or exposed, it will seriously harm their privacy and may endanger their lives. In order to encrypt data and establish perfectly alright access control for such sensitive information, attribute-based encryption (ABE) has typically been used. Traditional ABE, however, has a high processing overhead. As a result, an effective security system algorithm based on ABE and Fully Homomorphic Encryption (FHE) is developed to protect health-related data. ABE is a workable option for one-to-many communication and perfectly alright access management of encrypting data in a cloud environment. Without needing to decode the encrypted data, cloud servers can use the FHE algorithm to take valid actions on it. Because of its potential to provide excellent security with a tiny key size, elliptic curve cryptography (ECC) algorithm is also used. As a result, when compared to related existing methods in the literature, the suggested hybridized algorithm (ABE-FHE-ECC) has reduced computation and storage overheads. A comprehensive safety evidence clearly shows that the suggested method is protected by the Decisional Bilinear Diffie-Hellman postulate. The experimental results demonstrate that this system is more effective for devices with limited resources than the conventional ABE when the system’s performance is assessed by utilizing standard model

    Improved ciphertext-policy time using short elliptic curve Diffie–Hellman

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    Ciphertext-policy attribute-based encryption (CP-ABE) is a suitable solution for the protection of data privacy and security in cloud storage services. In a CP-ABE scheme which provides an access structure with a set of attributes, users can decrypt messages only if they receive a key with the desired attributes. As the number of attributes increases, the security measures are strengthened proportionately, and they can be applied to longer messages as well. The decryption of these ciphertexts also requires a large decryption key which may increase the decryption time. In this paper, we proposed a new method for improving the access time to the CP using a new elliptic curve that enables a short key size to be distributed to the users that allows them to use the defined attributes for encryption and decryption. Each user has a specially created key which uses the defined attributes for encryption and decryption based on the Diffie-Hellman method. After the implement, the results show that this system saves nearly half of the execution time for encryption and decryption compared to previous methods. This proposed system provides guaranteed security by means of the elliptic curve discrete logarithmic problem

    Attribute-based encryption for cloud computing access control: A survey

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    National Research Foundation (NRF) Singapore; AXA Research Fun

    A Framework for Uncertain Cloud Data Security and Recovery Based on Hybrid Multi-User Medical Decision Learning Patterns

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    Machine learning has been supporting real-time cloud based medical computing systems. However, most of the computing servers are independent of data security and recovery scheme in multiple virtual machines due to high computing cost and time. Also, this cloud based medical applications require static security parameters for cloud data security. Cloud based medical applications require multiple servers to store medical records or machine learning patterns for decision making. Due to high Uncertain computational memory and time, these cloud systems require an efficient data security framework to provide strong data access control among the multiple users. In this work, a hybrid cloud data security framework is developed to improve the data security on the large machine learning patterns in real-time cloud computing environment. This work is implemented in two phases’ i.e. data replication phase and multi-user data access security phase. Initially, machine decision patterns are replicated among the multiple servers for Uncertain data recovering phase. In the multi-access cloud data security framework, a hybrid multi-access key based data encryption and decryption model is implemented on the large machine learning medical patterns for data recovery and security process. Experimental results proved that the present two-phase data recovering, and security framework has better computational efficiency than the conventional approaches on large medical decision patterns

    Cloud Security in Crypt Database Server Using Fine Grained Access Control

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    Information sharing in the cloud, powered by good patterns in cloud technology, is rising as a guaranteeing procedure for permitting users to advantageously access information. However, the growing number of enterprises and customers who stores their information in cloud servers is progressively challenging users’ privacy and the security of information. This paper concentrates on providing a dependable and secure cloud information sharing services that permits users dynamic access to their information. In order to achieve this, propose an effective, adaptable and flexible privacy preserving information policy with semantic security, by using Cipher text Policy Element Based Encryption (CP-EBE) consolidated with Character Based Encryption (CBE) systems. To ensure strong information sharing security, the policy succeeds in protecting the privacy of cloud users and supports efficient and secure dynamic operations, but not constrained to, file creation, user revocation. Security analysis demonstrates that the proposed policy is secure under the generic bi- linear group model in the random oracle model and enforces fine-grained access control, full collusion resistance and retrogressive secrecy. Furthermore, performance analysis and experimental results demonstrate that the overheads are as light as possible

    Dynamic Policy Update on Cloud for File Access

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    In today’s era of digitalization everyone stores and access data online. Cloud computing has become prominent in data storage and access any where globally, but there is concern by data owners regarding data ownership. It is monotonous to assign access rights and simultaneously provide security in real time is a concern. To resolve this issue of access control in recent times Attribute based encryption method is widely preferred. One of the most popular method to handle access rights is by used is Attribute-based Encryption (ABE) method, the two ways for performing the implementation of ABE are ciphertext-policy and key-policy ABE. One of the widely practiced methods of safe communication is through cryptography. In this work we are proposing a method to handle access rights dynamically on the outlines of Ciphertext-policy attribute-based encryption (CP-ABE) scheme along with this we are using two symmetric encryption algorithm namely AES and Serpent for providing better security to the system. This work implements a new policy update method which helps to manage data access control in the dynamic policy update for data in the cloud storage. In this, same input key is utilized for the both encryption and decryption operation. Here two types of files are handled as an input such as Text file and image file. In experimental result, comparison of both algorithms is shown with the help of graphs with different parameters such as Time, Number of files, file size. And we have also shown the comparison of system having dynamic update policy and system with out in tabular form. We have also shown the comparative analysis of both algorithms that shows SERPENT encryption algorithm gives superior performance in Encryption

    Data Access in Multiauthority Cloud Storage: Expressive and Revocable Data Control System

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    ABSTRACT Cloud computing is rising enormously due to its advantages and the adaptable storage services being provided by it. Because of this, the number of users has reached the top level. The users will share the sensitive data through the cloud. Furthermore, the user can\u27t trust the untrusted cloud server. Subsequently, the data access control has turned out to be extremely challenging in cloud storage framework. In existing work, revocable data access control scheme proposed for multi-authority cloud storage frameworks which supports the access control in light of the authority control. The authorized users who have desirable attributes given by various authorities can access the data. However, it couldn\u27t control the attacks which can happen to the authorized user who is not having desirable attributes. In this work, they propose a new algorithm named Improved Security Data Access Control which beats the issue exists in the existing work. And furthermore, incorporates the efficient attribute revocation strategy for multi-authority cloud storage. Keywords: Access control, multi-authority, attribute revocation, cloud storage

    Secure publish-subscribe protocols for heterogeneous medical wireless body area networks

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    Security and privacy issues in medical wireless body area networks (WBANs) constitute a major unsolved concern because of the challenges posed by the scarcity of resources in WBAN devices and the usability restrictions imposed by the healthcare domain. In this paper, we describe a WBAN architecture based on the well-known publish-subscribe paradigm. We present two protocols for publishing data and sending commands to a sensor that guarantee confidentiality and fine-grained access control. Both protocols are based on a recently proposed ciphertext policy attribute-based encryption (CP-ABE) scheme that is lightweight enough to be embedded into wearable sensors. We show how sensors can implement lattice-based access control (LBAC) policies using this scheme, which are highly appropriate for the eHealth domain. We report experimental results with a prototype implementation demonstrating the suitability of our proposed solution.This work was supported by the MINECO grant TIN2013-46469-R (SPINY: Security and Privacy in the Internet of You)

    SEM-ACSIT:Secure and Efficient Multiauthority Access Control for IoT Cloud Storage

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    Data access control in a cloud storage system is regarded as a promising technique for enhanced efficiency and security utilizing a ciphertext-policy attribute-based encryption (CP-ABE) approach. However, due to a large number of data users as well as limited resources and heterogeneity of data devices in Internet of Things (IoT), existing access control schemes for the cloud storage are not effectively applicable to IoT applications. In this article, we construct a new CP-ABE-based storage model for data storing and secure access in a cloud for IoT applications. Our new framework introduces an attribute authority management (AAM) module in the cloud storage system functioned as an agent that provides a user-friendly access control and highly reduces the storage overhead of public keys. Then, we propose a novel secure and efficient multiauthority access control scheme of the cloud storage system for IoT, namely, SEM-ACSIT, which obtains both backward security and forward security when an attribute of a user is revoked. By exploiting encryption outsourcing, simplified key structuring and the AAM module, the computational overhead of a user is immensely decreased. Moreover, a user access control list (UACL) in the cloud server is constructed newly to support authorization access for a specific user. The analysis and simulation results demonstrate that our SEM-ACSIT scheme achieves powerful security with less computational overhead and lower storage costs than the existing schemes
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