Memory-Efficient Trust Management for IoT Nodes Enabling Secure Communication in Trusted Environments

The Internet of Things (IoT) is changing quickly, so making sure that gadgets that are linked can talk to each other safely is very important. This paper describes a new way to handle trust that is specifically made for IoT nodes that work in safe settings. Conventional models frequently have a parcel of additional memory needs and are difficult to compute, which is made more regrettable by IoT gadgets that do not have a part of assets. Our proposed approach bargains with these issues by employing a belief administration framework that doesn't utilize a parcel of memory and finds an adjustment between security needs and the restricted assets that IoT hubs have. The foremost inventive thing around our strategy is that it can alter belief levels on the fly based on modern data and past experiences. Our framework takes up as small memory as conceivable whereas still having solid security measures since it employs lightweight cryptography conventions and quick information structures. This lets Internet of Things (IoT) gadgets utilize secure communication strategies without abating them down or making them less dependable. Context-aware belief assessment could be a key portion of our framework. This implies that belief levels are continually changed based on real-time encompassing variables and the way hubs are connected with each other. This adaptable alter makes beyond any doubt that belief choices remain in line with changing working conditions and threat scenarios. We moreover made beyond any doubt that our strategy works well with current IoT plans, permitting distinctive sorts of systems to work together and develop. We demonstrate that our system works in a wide range of IoT application cases by running a part of models and real-world tests on it. This study shows an easy-to-use and expandable way to improve trust management in IoT settings, with a focus on memory efficiency without losing safety. By using our approach, IoT stakeholders can reduce the risks that come with old trust models. This will make IoT environments more reliable and adaptable in the future.

Authors

Publication Details

Journal
Advances in Nonlinear Variational Inequalities
Published
2024-08-23
DOI
https://doi.org/10.52783/anvi.v27.1345
Primary Topic
Cloud Data Security Solutions
Type
article
Field-Weighted Citation Impact
0.00
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article

Memory-Efficient Trust Management for IoT Nodes Enabling Secure Communication in Trusted Environments

Satish Kamble
Advances in Nonlinear Variational Inequalities
Cloud Data Security Solutions
article

Memory-Efficient Trust Management for IoT Nodes Enabling Secure Communication in Trusted Environments

Satish Kamble
article en

Abstract

The Internet of Things (IoT) is changing quickly, so making sure that gadgets that are linked can talk to each other safely is very important. This paper describes a new way to handle trust that is specifically made for IoT nodes that work in safe settings. Conventional models frequently have a parcel of additional memory needs and are difficult to compute, which is made more regrettable by IoT gadgets that do not have a part of assets. Our proposed approach bargains with these issues by employing a belief administration framework that doesn't utilize a parcel of memory and finds an adjustment between security needs and the restricted assets that IoT hubs have. The foremost inventive thing around our strategy is that it can alter belief levels on the fly based on modern data and past experiences. Our framework takes up as small memory as conceivable whereas still having solid security measures since it employs lightweight cryptography conventions and quick information structures. This lets Internet of Things (IoT) gadgets utilize secure communication strategies without abating them down or making them less dependable. Context-aware belief assessment could be a key portion of our framework. This implies that belief levels are continually changed based on real-time encompassing variables and the way hubs are connected with each other. This adaptable alter makes beyond any doubt that belief choices remain in line with changing working conditions and threat scenarios. We moreover made beyond any doubt that our strategy works well with current IoT plans, permitting distinctive sorts of systems to work together and develop. We demonstrate that our system works in a wide range of IoT application cases by running a part of models and real-world tests on it. This study shows an easy-to-use and expandable way to improve trust management in IoT settings, with a focus on memory efficiency without losing safety. By using our approach, IoT stakeholders can reduce the risks that come with old trust models. This will make IoT environments more reliable and adaptable in the future.

Advances in Nonlinear Variational InequalitiesVol. 27(2)
Openalex Percentile: Top 68%
Cloud Data Security Solutions
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Memory-Efficient Trust Management for IoT Nodes Enabling Secure Communication in Trusted Environments — Satish Kamble · Advances in Nonlinear Variational Inequalities (2024) | TGRS Research Map | TGRS