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EN
Ciphertext policy attribute-based encryption (CPABE) is one of the efficient implementations of encrypted access control scheme for cloud computing. Though multiple implementations of CPABE exist, there are some issues that need to be addressed, including efficient revocation approach, decryption time, storage cost etc. In this paper, an efficient scheme that incorporates a hierarchical access structure, outsourced decryption, as well as user and attribute revocation is presented. The hierarchical access structure is utilized to encrypt multiple data using one common access structure and makes the encryption process more efficient. The outsourcing server is used to perform partial decryption, so that all heavy computations are performed by this server and less overhead is incurred by the data user. The proposed framework also integrates the evaluation of trustworthiness of data users and service providers to ensure trusted and encrypted access control procedures. The paper also presents an analysis of the time required for performing different operations. Simulation results show that the proposed scheme outperforms the existing approaches.
EN
Cloud computing is being rapidly adopted by many organizations from different domains and large amounts of data is stored in the cloud. In order to ensure data security, the attribute-based access control mechanism has been emerging recently as a fine-grained access control model that grants access based on the data user’s attributes. In this model, the data owner builds the access policy using the attributes of the data users and access to the data is granted only if the requirements of such an access policy are satisfied. Ciphertext policy-based attribute-based encryption (CPABE) is one of the most widely used methods for providing encrypted access control. Complex, time consuming and costly paring operations are the major issue with the CPABE method. Hence, another efficient method is needed to reduce the data user’s overhead while decrypting data. This paper presents an efficient method consisting in outsourcing decryption operations to a third-party server, so that complex operations may be performed by that machine with only some simple calculations left on the data user’s side. The concept of a hierarchical access structure is also integrated with the traditional CPABE technique. The hierarchical approach enables the data owner to encrypt multiple data using a single common hierarchical access structure. This allows the user to decrypt only the relevant part of ciphertext, depending on which fragment of the hierarchical access structure is satisfied. The paper evaluates also the performance of the proposed model in terms of time and storage cost.
EN
The Internet of Things has a set of smart objects with smart connectivity that assists in monitoring real world environment during emergency situations. It could monitor the various applications of emergency situations such as road accidents, criminal acts including physical assaults, kidnap cases, and other threats to people’s way of life. In this work, the proposed work is to afford real time services to users in emergency situations through Convolutional Neural Networks in terms of efficiency and reliable services. Finally, the proposed work has simulated with respect to the performance parameters of the proposed scheme like the probability of accuracy and processing time.
EN
Efficient resource management is a challenging task in distributed systems, such as the Internet of Things, fog, edge, and cloud computing. In this work, we present a broad overview of the Internet of Things ecosystem and of the challenges related to managing its resources. We also investigate the need for efficient resource management and the guidelines given/suggested by Standard Development Organizations. Additionally, this paper contains a comprehensive survey of the individual phases of resource management processes, focusing on resource modeling, resource discovery, resource estimation, and resource allocation approaches based on performance parameters or metrics, as well as on architecture types. This paper presents also the architecture of a generic resource management enabler. Furthermore, we present open issues concerning resource management, pointing out the directions of future research related to the Internet of Things.
EN
A Cognitive Internet of Things (CIoT) is a brand of Internet of Things (IoT) with cognitive and agreeable mechanisms, which are incorporated to advance performance and accomplish insights into real world environments. CIoT can perceive present system’s conditions, analyze the apparent information, make smart choices, and increase the network performance. In this survey paper, we present classifications of data perception techniques used in CIoT. This paper also compares the data perception works against energy consumption, network life-time, resource allocation, and throughput, as well as quality of data and delay. In addition, simulation tools for IoT and their performance are discussed. Finally, we provide the model of cognitive agent-based data perception in CIoT for future research and development, which ensures the network performance in terms of reliability, energy efficient, accuracy, scalable, fault tolerant, and quality of data.
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