Cloud-edge data encryption in the internet of vehicles using Zeckendorf representation

Cloud computing is an on-demand availability of computing resources. The current cloud computing environment uses different algorithms for its security; RC4 is one of them. However, due to the serial implementation of RC4 over cloud computing, the process of encryption and data transmission is badly affected by the factors of poor latency. This research is proposed to cover this factor by implementing a parallel RC4 algorithm in a cloud computing environment. The parallel RC4 model has been developed in web-based architecture relevant to the cloud computing environment. The method processed data simultaneously in four parallel pipelines encrypted through the RC4 algorithm. The proposed method used RC4 algorithms’ parallel implementation to encrypt and decrypt the data. The proposed method increases the efficiency of data encryption and decryption and transmission over a cloud environment using four pipelines at once. These four pipelines receive data and encrypt them using a key and then merge those four streams into a single cipher. These four pipelines enhance the speed of communication over cloud and solve the latency issue majorly. Data sending from node devices to cloud servers is divided into four equal streams and then encrypted using RC4 distinctly but parallel. Then after the roaming, the data are again first combined and then decrypted using the RC4 algorithm. The sample data sets are evaluated on the criteria of the starting time and ending time of the encryption and decryption of data. Results show that the proposed method is able to enhance the speed of the whole process up to average 3.7% due to the implementation of parallel technique and had reduced the time notably. The future work on this research involves enhancement of security process of RC4 algorithm since it can be breached easily.

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An Intelligent Data Retrieving Technique and Safety Measures for Sustainable Cloud Computing

Kumar,

Chatterjee

et al. 2024

Improving Security, Privacy, and Trust in Cloud Computing

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Data refers to raw facts and figures. After processing data, the information is created. Information like facts or statistics that can be recorded, stored, and analysed can be in various forms such as text, numbers, images, audio, or video. The amount of data generated every day in the data-driven world of today makes it nearly difficult to keep it all locally. Cloud services are being used by so many people and businesses to store these massive and hefty volumes of data on cloud servers. Additionally, as the need for cloud computing grows, so does the need for data recovery methods and services. The ability to recover data and information from the backup server when the primary server is down is the primary goal of recovery services and technologies. A secondary server to hold backups for the primary cloud server will be more expensive to add than the primary server itself, which is already quite expensive and time-consuming to build. The goal of this chapter is to provide realistic, cost-effective solutions to this urgent problem.

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Cloud-edge data encryption in the internet of vehicles using Zeckendorf representation

Cited by 3 publications

References 12 publications

Simulation of Routing Protocols for IoV in Real-Time Mobility Model Environment

Simulation of Routing Protocols for IoV in Real-Time Mobility Model Environment

Parallel Implementation of RC4 Data Encryption Method for Cloud Computing

An Intelligent Data Retrieving Technique and Safety Measures for Sustainable Cloud Computing

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