SECURE AND EFFICIENT DATA MANAGEMENT IN FOG-ENABLED IOT NETWORKS

Abstract

One of the main concerns with cloud computing is security. AII of the data from different Internet of Things (loT) devices may be processed and stored with the use of cloud computing. The loT environment's computational and storage load can be lessened with the use of fog computing. lt makes use of cloud computing benefits that are situated on the application's edge, potentially resolving numerous security concerns related to cloud-loT architecture. To improve data security in the loT, a plan that combines cloud architecture with loT fog has been developed in this work. The massive amount of data generated by loT devices is computed in the fog computing layer. The AES technique is used to encrypt the calculated data. To improve data security, the data is divided. An effective data compression strategy is used to save the partitioned data in the cloud environment. The suggested plan is safe from known risks and assaults, according to the security study. According to the experimental findings, the fog layer is capable of carrying out nearly all compute operations, including data compression, encryption, decryption, partitioning, and reassembling.

Specification

The following technical description goes into extensive detail about both the invention itself and the process in which it is to be carried out.

An industry predominantly depends on data, to fulfill their business requirements and needs. Industrial applications and devices are connected to the Internet of Things (loT) to ensure data availability which indeed aids in decision making. loT provides a data analysis task from the generated data and resolves many major problems in the organization. As per the survey, the number of devices that are associated with the Internet of Things will reach 75 billion within the next decade. With the rapid increase of loT devices brings many challenges in the forthcoming era. Data generated by every loT device is voluminous and transmitting the massive volume of data to the cloud will probably increase the cost in terms of storage, time, and energy consumption. Thus Fog computing resolves all these potential issues and provides a solution for the cloud computing challenges like interoperability, availability, reliability, security and privacy. Fog computing has more benefits over cloud computing. It provides various effective mechanisms to compute the loT data locally on the edge side of the network. Cloud computing is a centralized network whereas fog computing is decentralized in nature and it works in-between the loT layer and

the remote servers. Fog nodes have full control over data that can process and
manage the data locally
4.2 FIELD OF INVENTION
An approach that integrates loT-fog -cloud architecture has been designed to
enhance data security in the loT.
4.3 DISCUSSION OF THE RELATED ART
loT application receives heterogeneous data from various resources. The data processing and achieving data security to a huge volume of data is a very difficult task. To enhance data security in the loT layer, many security algorithms are proposed and implemented. The main demerit in the loT devices is the storage restriction which will collapse the overall operation. One of the major challenges is to equalize the functionality and the security parameters in the node-side itself. But data encryption required more disk space in the noded as compared to the other computations. It reduces the performance of the loT environment without adequate storage. All these requirements and the challenges lead the path to the Fog computing for better enhancement in loT and other domains. Fog computing act as a bridge between a remote data center and the loT sensor nodes /it brings remote data center closer to the loT application. Fog computing enables many benefits among all the loT


applications and other domains by the reduction in bandwidth and latency.
Though it provides many advantages, it has some challenges in security
28-Qct-2024/130708/202441082096/Form 2(Title Page)
4.4 SUMMARY OF INVENTION
In this work, the major challenges in loT security have been identified and resolved with the help of the proposed Fog based framework. To enhance data security effectively in loT application, the framework used both data encryption and data partitioning technique uses AES and Shamir cipher shares algorithm.
To achieve storage optimization in the cloud layer, Huffman compression technique is used. Further, the security analysis has been evaluated based on CIA properties. The result proved that the proposed framework takes less computation time, latency, network usage, and less storage space in the cloud.
The framework also meets the necessary security requirements. 4.4 DETAILED DISCRIPTION OF THE INVENTON
The proposed framework mainly deals with data security during data transmission in the network and it focuses on storage optimization in the cloud environment. The proposed framework consists of three-layer and its operations detailed as follows. It is the first .layer of the framework which consists of sensors, communication devices, and other network devices. Each device and sensors in the loT layer has different functionality and purpose. Each


device generates enormous data for every second. Adding security to the loT layer is a very challenging task in every loT application, as the device has limited space and computation. Hence in the proposed framework, it enhances the security of the loT environment through fog computing. The sensors generate the data continuously and It is transmitted directly to the fog layer before it
transmitted to the cloud layer.
Cloud computing faces many challenges in terms of security in loT application, that can be minimized using Fog computing. Fog brings the cloud closer with all the cloud functionality in an effective way. The fog layer is the intermediate layer of the proposed framework. The layer fetches the data from the loT layer.
The fog layer consists of three operations to enhance security.
After the data partitioning, the partitioned shares send to the cloud servers to store the shares. The major problem in the partition is the size. Each share size is equal to the original file size hence it dramatically increase the cloud storage.
To overcome these issues, the framework integrates the storage optimization technique by using Huffman code compression. Using Huffman code compression the size of the file reduces to half the size. Hence all the partitioned 'n' share size is approximately equal to the original file size.
The proposed framework resolves the first issue, partition data encryption in the data reduction phase, key Storage issues are overcome in the data partitioned phase. Finally, the storage optimization problem is resolved using the Huffman code compression technique in the cloud layer.

Claim 1: designs a system that integrates loT-fog -cloud architecture to enhance data security in the. loT.
Claim 2: Enhance the data security and effective data storage in the cloud

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