Context-Aware Device Classification and Clustering for Smarter and Secure Connectivity in Internet of Things

Q2 Engineering
Priyanka More, None Sachin Sakhare
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引用次数: 0

Abstract

With the increasing prevalence of the Internet of Things (IoT), there is a growing need for effective access control methods to secure IoT systems and data. Traditional access control models often prove inadequate when dealing with the specific challenges presented by IoT, characterized by a variety of heterogeneous devices, ever-changing network structures, and diverse contextual elements. Managing IoT devices effectively is a complex task in maintaining network security.This study introduces a context-driven approach for IoT Device Classification and Clustering, aiming to address the unique characteristics of IoT systems and the limitations of existing access control methods. The proposed context-based model utilizes contextual information such as device attributes, location, time, and communication patterns to dynamically establish clusters and cluster leaders. By incorporating contextual factors, the model provides a more accurate and adaptable clustering mechanism that aligns with the dynamic nature of IoT systems. Consequently, network administrators can configure dynamic access policies for these clusters.
面向物联网中更智能、更安全连接的环境感知设备分类和聚类
随着物联网(IoT)的日益普及,越来越需要有效的访问控制方法来保护物联网系统和数据。传统的访问控制模型在处理物联网所带来的具体挑战时往往被证明是不够的,物联网的特点是各种异构设备、不断变化的网络结构和不同的上下文元素。有效管理物联网设备是维护网络安全的一项复杂任务。本研究引入了一种上下文驱动的物联网设备分类和聚类方法,旨在解决物联网系统的独特特征和现有访问控制方法的局限性。所提出的基于上下文的模型利用诸如设备属性、位置、时间和通信模式等上下文信息来动态地建立集群和集群领导者。通过结合上下文因素,该模型提供了一种更准确、适应性更强的集群机制,与物联网系统的动态特性保持一致。因此,网络管理员可以为这些集群配置动态访问策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.00
自引率
0.00%
发文量
15
审稿时长
10 weeks
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