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  • Open Access

    ARTICLE

    Attribute Reduction on Decision Tables Based on Hausdorff Topology

    Nguyen Long Giang1, Tran Thanh Dai2, Le Hoang Son3, Tran Thi Ngan4, Nguyen Nhu Son1, Cu Nguyen Giap5,*

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3097-3124, 2024, DOI:10.32604/cmc.2024.057383 - 18 November 2024

    Abstract Attribute reduction through the combined approach of Rough Sets (RS) and algebraic topology is an open research topic with significant potential for applications. Several research works have introduced a strong relationship between RS and topology spaces for the attribute reduction problem. However, the mentioned recent methods followed a strategy to construct a new measure for attribute selection. Meanwhile, the strategy for searching for the reduct is still to select each attribute and gradually add it to the reduct. Consequently, those methods tended to be inefficient for high-dimensional datasets. To overcome these challenges, we use the… More >

  • Open Access

    ARTICLE

    Two-Stage Client Selection Scheme for Blockchain-Enabled Federated Learning in IoT

    Xiaojun Jin1, Chao Ma2,*, Song Luo2, Pengyi Zeng1, Yifei Wei1

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2317-2336, 2024, DOI:10.32604/cmc.2024.055344 - 18 November 2024

    Abstract Federated learning enables data owners in the Internet of Things (IoT) to collaborate in training models without sharing private data, creating new business opportunities for building a data market. However, in practical operation, there are still some problems with federated learning applications. Blockchain has the characteristics of decentralization, distribution, and security. The blockchain-enabled federated learning further improve the security and performance of model training, while also expanding the application scope of federated learning. Blockchain has natural financial attributes that help establish a federated learning data market. However, the data of federated learning tasks may be… More >

  • Open Access

    ARTICLE

    Reversible Data Hiding Algorithm in Encrypted Images Based on Adaptive Median Edge Detection and Ciphertext-Policy Attribute-Based Encryption

    Zongbao Jiang, Minqing Zhang*, Weina Dong, Chao Jiang, Fuqiang Di

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1123-1155, 2024, DOI:10.32604/cmc.2024.055120 - 15 October 2024

    Abstract With the rapid advancement of cloud computing technology, reversible data hiding algorithms in encrypted images (RDH-EI) have developed into an important field of study concentrated on safeguarding privacy in distributed cloud environments. However, existing algorithms often suffer from low embedding capacities and are inadequate for complex data access scenarios. To address these challenges, this paper proposes a novel reversible data hiding algorithm in encrypted images based on adaptive median edge detection (AMED) and ciphertext-policy attribute-based encryption (CP-ABE). This proposed algorithm enhances the conventional median edge detection (MED) by incorporating dynamic variables to improve pixel prediction… More >

  • Open Access

    ARTICLE

    Automatic Generation of Attribute-Based Access Control Policies from Natural Language Documents

    Fangfang Shan1,2,*, Zhenyu Wang1,2, Mengyao Liu1,2, Menghan Zhang1,2

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3881-3902, 2024, DOI:10.32604/cmc.2024.055167 - 12 September 2024

    Abstract In response to the challenges of generating Attribute-Based Access Control (ABAC) policies, this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents. This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model. The manual retrieval and analysis involved in this transition are inefficient, prone to errors, and costly. Most organizations have high-level specifications defined for security policies that include a set of access control policies, which often exist in the form of natural language documents. Utilizing… More >

  • Open Access

    ARTICLE

    Morphometric Attributes of Two Native Forage Species According to Water Source Distance in Semiarid Central Grasslands of Argentina

    Carla Etel Suárez1,*, María Sol Rossini1,3, Ernesto Francisco Atilio Morici1, Héctor Daniel Esterlich1,2

    Phyton-International Journal of Experimental Botany, Vol.93, No.8, pp. 2063-2074, 2024, DOI:10.32604/phyton.2024.053193 - 30 August 2024

    Abstract The semiarid grasslands of Argentina’s central region have been modified by domestic livestock grazing, both in their composition and structure. The increase in the proportion of woody and non-forage species and the decrease in forage species are some of the most evident results of this process. There is limited available information about the effect of differential grazing pressures on morphometric attributes of native species, and it also depends on the life histories of the species in this grassland. The objective of this work was to evaluate some morphometric aspects in the grasses Poa ligularis Nees ex… More >

  • Open Access

    ARTICLE

    Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

    Xiaoqin Ma1,2, Jun Wang1, Wenchang Yu1, Qinli Zhang1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2063-2083, 2024, DOI:10.32604/cmc.2024.049147 - 15 May 2024

    Abstract The presence of numerous uncertainties in hybrid decision information systems (HDISs) renders attribute reduction a formidable task. Currently available attribute reduction algorithms, including those based on Pawlak attribute importance, Skowron discernibility matrix, and information entropy, struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values, and attributes with fuzzy boundaries and abnormal values. In order to address the aforementioned issues, this paper delves into the study of attribute reduction within HDISs. First of all, a novel metric based on the decision attribute is introduced to solve… More >

  • Open Access

    ARTICLE

    A Lightweight, Searchable, and Controllable EMR Sharing Scheme

    Xiaohui Yang, Peiyin Zhao*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1521-1538, 2024, DOI:10.32604/cmc.2024.047666 - 25 April 2024

    Abstract Electronic medical records (EMR) facilitate the sharing of medical data, but existing sharing schemes suffer from privacy leakage and inefficiency. This article proposes a lightweight, searchable, and controllable EMR sharing scheme, which employs a large attribute domain and a linear secret sharing structure (LSSS), the computational overhead of encryption and decryption reaches a lightweight constant level, and supports keyword search and policy hiding, which improves the high efficiency of medical data sharing. The dynamic accumulator technology is utilized to enable data owners to flexibly authorize or revoke the access rights of data visitors to the More >

  • Open Access

    ARTICLE

    A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

    Hao Jiang1, Yuerong Liao1, Dongdong Zhao2, Wenjian Luo3, Xingyi Zhang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1045-1075, 2024, DOI:10.32604/cmes.2024.048653 - 16 April 2024

    Abstract Due to the presence of a large amount of personal sensitive information in social networks, privacy preservation issues in social networks have attracted the attention of many scholars. Inspired by the self-nonself discrimination paradigm in the biological immune system, the negative representation of information indicates features such as simplicity and efficiency, which is very suitable for preserving social network privacy. Therefore, we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks, called AttNetNRI. Specifically, a negative survey-based method is developed to disturb the relationship between nodes in the… More >

  • Open Access

    ARTICLE

    A Blockchain and CP-ABE Based Access Control Scheme with Fine-Grained Revocation of Attributes in Cloud Health

    Ye Lu1,*, Tao Feng1, Chunyan Liu2, Wenbo Zhang3

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2787-2811, 2024, DOI:10.32604/cmc.2023.046106 - 27 February 2024

    Abstract The Access control scheme is an effective method to protect user data privacy. The access control scheme based on blockchain and ciphertext policy attribute encryption (CP–ABE) can solve the problems of single—point of failure and lack of trust in the centralized system. However, it also brings new problems to the health information in the cloud storage environment, such as attribute leakage, low consensus efficiency, complex permission updates, and so on. This paper proposes an access control scheme with fine-grained attribute revocation, keyword search, and traceability of the attribute private key distribution process. Blockchain technology tracks… More >

  • Open Access

    ARTICLE

    A Blockchain-Based Access Control Scheme for Reputation Value Attributes of the Internet of Things

    Hongliang Tian, Junyuan Tian*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1297-1310, 2024, DOI:10.32604/cmc.2024.047058 - 30 January 2024

    Abstract The Internet of Things (IoT) access control mechanism may encounter security issues such as single point of failure and data tampering. To address these issues, a blockchain-based IoT reputation value attribute access control scheme is proposed. Firstly, writing the reputation value as an attribute into the access control policy, and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control; Secondly, storing a large amount of resources from the Internet of Things in Inter Planetary File System (IPFS) to improve system More >

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