Unstructured Text Resource Access Control Attribute Mining Technology Based on Convolutional Neural Network

Liu, Aodi; Du, Xuehui; Wang, Na

doi:10.1109/access.2019.2907815

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…In order to process an image for recognition, several parameters are collected from that image's features and compared with the existing library. A similarity value is obtained based on the proposed model, which is then used to identify the identity based on the calculated value for the face [35]. Fig.…”

Section: System Designmentioning

confidence: 99%

A Privacy-Preserving System Design for Digital Presence Protection

Yocam¹,

Alomari²,

Gwanmeh³

et al. 2023

Computers, Materials &Amp; Continua

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A person's privacy has become a growing concern, given the nature of an expansive reliance on real-time video activities with video capture, stream, and storage. This paper presents an innovative system design based on a privacy-preserving model. The proposed system design is implemented by employing an enhanced capability that overcomes today's single parameterbased access control protection mechanism for digital privacy preservation. The enhanced capability combines multiple access control parameters: facial expression, resource, environment, location, and time. The proposed system design demonstrated that a person's facial expressions combined with a set of access control rules can achieve a person's privacy-preserving preferences. The findings resulted in different facial expressions successfully triggering a person's face to be blurred and a person's privacy when using a real-time video conferencing service captured from a webcam or virtual webcam. A comparison analysis of capabilities between existing designs and the proposed system design shows enhancement of the capabilities of the proposed system. A series of experiments exercising the enhanced, real-time multi-parameterbased system was shown as a viable path forward for preserving a person's privacy while using a webcam or virtual webcam to capture, stream, and store videos.

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Section: System Designmentioning

confidence: 99%

A Privacy-Preserving System Design for Digital Presence Protection

Yocam¹,

Alomari²,

Gwanmeh³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Used in # of studies Percentage ABAC [23], [24], [25], [26], [12], [27], [28], [29], [10], [30], [31], [32], [33], [34], [13], [35], [36] and MLBAC were each used in one study (2%). Some studies may have employed multiple access control models, such as [25], which utilized both ABAC and ReBAC.…”

Section: Ac Modelmentioning

confidence: 99%

“…Metrics like AUC, ROC, and FNR were employed in two studies each, and the remaining metrics were reported only once. It is important to note that multiple [23], [41], [44], [53], [45], [24], [42], [70], [39], [56], [46], [26], [71], [64], [40], [28], [43], [66], [10], [30], [31], [47], [62], [33], [76], [13], [37], [67] 28 45 % Accuracy [52], [53], [70], [39], [65], [12], [71], [72], [64], [40], [57], [28], [43], [66], [59], [10], [61], [38], [48], [8], [62],…”

Section: H Performance Metrics (Rq8)mentioning

confidence: 99%

Exploring the Role of Machine Learning in Enhancing Access Control Systems: A Comprehensive Review

Ait el hadj

2023

IJCDS

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Access control (AC) systems are crucial for safeguarding sensitive data and resources, yet the increasing complexity of dynamic environments has underscored the need for more accurate and efficient solutions. Therefore, there is a growing need to enhance the accuracy, efficiency, and decision-making capabilities of AC systems. Machine learning (ML) techniques offer promising solutions to address these challenges and automate access control processes. This paper conducts a systematic review of ML techniques in AC systems, involving a comprehensive analysis covering the identification and classification of ML models and their specific applications. Through a meticulous examination of 62 relevant studies published between 2000 and 2023, the review reveals a predominant focus on innovative solutions and adaptations to enhance access control decision-making. Comparative studies play a significant role in assessing different ML approaches, with a focus on identifying the most effective methods for addressing access control challenges. Notably, Attribute-Based Access Control (ABAC) and Role-Based Access Control (RBAC) emerge as the predominant models, while Support Vector Machine (SVM) tops the list as the most commonly employed ML technique, followed by Random Forest (RF) and Decision Tree (DT). The review evaluates the performance and effectiveness of ML models in AC systems, highlighting their strengths and limitations. Additionally, it addresses significant challenges in the field and identifies potential directions for future research. This systematic review provides valuable insights into the current state of ML-based access control systems, fostering further advancements in this vital domain.

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“…In this paper [1] author proposed a multidimensional hybrid feature strategy for text resource properties. This technique completely figures the qualities of characteristics themselves, the connections among attributes, and the connection between…”

Section: Literature Reviewmentioning

confidence: 99%

An Effective Attributes Mining for Larger Dataset using Neural Network

Patil¹,

Powar²

2020

IJERT

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The present world is computerized world and this is necessary to utilize computerized information, for example, video, sound, pictures and so forth in different fields for different purposes. Right now, plays imperative job in each part of business, for example, business pictures, satellite pictures, and clinical pictures, etc. Image mining is testing field which broadens conventional information mining from organized information to unstructured information such as picture information. In the attribute based access control (ABAC) model, properties are the reason for controlling access to information assets. A Convolutional neural network (CNN) is a neural system that has at least one convolutional layers and are utilized for the most part for picture preparing, characterization, division and furthermore for other auto associated information. Steganography is the procedure of concealing mystery information inside an image or message so as to stay away from location; the mystery information is then removed at its goal. This paper covers literature survey of image mining techniques in CNN.

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Unstructured Text Resource Access Control Attribute Mining Technology Based on Convolutional Neural Network

Cited by 6 publications

References 16 publications

A Privacy-Preserving System Design for Digital Presence Protection

A Privacy-Preserving System Design for Digital Presence Protection

Exploring the Role of Machine Learning in Enhancing Access Control Systems: A Comprehensive Review

An Effective Attributes Mining for Larger Dataset using Neural Network

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