Enhancing data security using global mutation based novel artificial immune network optimization in public cloud storage system

Kaliyamoorthy, Priyadharshini; Ramalingam, A.

doi:10.1002/ett.4390

Cited by 4 publications

(3 citation statements)

References 43 publications

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“…It becomes a difficult effort for the user to ensure that the output had safe. 25 Therefore, an innovative artificial immune network optimization strategy for RSA cryptosystems was proposed in this paper. A global mutation-based new artificial immune network optimization (GM-NAINO) was utilized to optimize key and high network usage.…”

Section: Related Workmentioning

confidence: 99%

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Improved secure dynamic bit standard technique for a private cloud platform to address security challenges

Gagged

Murugaiyan

2022

J. Electron. Imag.

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The numerous technologies and procedures used to safeguard private cloud infrastructure are private cloud security. Despite multitenant public cloud environments, resources are dedicated to individual companies in a private cloud. Cloud computing uses several data security mechanisms, including authentication and identification, access control, encryption, secure deletion, integrity checking, and data masking. Cloud computing relies heavily on security and traffic management. Because data must be transferred from a local computer to a remote computer when using a cloud computing service, data protection is becoming an increasingly important security problem. Research on cloud computing-based secure dynamic bit standard (CC-SDBS) technology has increased data security. This technique's cryptographic algorithms (CA) improve cloud computing security. As a result of the private cloud security level algorithm (PCSLA), the client's private data can be easily accessed in the cloud. For the client's private cloud data, PCSLA provides dynamic security measures. Cloud computing applications can use the tests' better data security in the future. The proposed algorithm's testing results have shown a noticeable improvement in cipher size and execution time compared with other commonly used cloud computing. Numerical results revealed that CC-SDBS improved average energy consumption by 20%, average network latency by 25%, average key generation time analysis by 4.3%, and average network use by 15%.

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Section: Related Workmentioning

confidence: 99%

“…While virtualization and multitenancy provide a few security issues, the most common ones are communication and isolation. It becomes a difficult effort for the user to ensure that the output had safe 25 . Therefore, an innovative artificial immune network optimization strategy for RSA cryptosystems was proposed in this paper.…”

Section: Related Workmentioning

confidence: 99%

Improved secure dynamic bit standard technique for a private cloud platform to address security challenges

Gagged

Murugaiyan

2022

J. Electron. Imag.

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“…Even though the integration looks good, it must be tested with many types of work. Using global mutation in artificial immune network optimization, Kaliyamoorthy and Ramalingam 30 developed a new way to keep data safe in public cloud storage. Even though it has potential, the amount of work it takes is still a worry.…”

Section: Introductionmentioning

confidence: 99%

Swarm Intelligence with a Chaotic Leader and a Salp algorithm: HDFS optimization for reduced latency and enhanced availability

Jagadish Kumar,

Dhinakaran,

Naresh Kumar

et al. 2024

Concurrency and Computation

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SummaryThe Hadoop distributed file system (HDFS) effectively manages data by segmenting it into blocks distributed across DataNodes in its cluster. While default block sizes in Hadoop 2.x and 1.x are 128 and 64 MB, respectively, they can be customized for larger files. HDFS ensures data reliability by replicating blocks across multiple DataNodes, but this can introduce high latency in cloud storage during heavy network traffic, particularly in big data processing. To address this, we introduce swarm intelligence with a chaotic leader and a salp (SI‐CLS) optimization algorithm. This algorithm reduces network traffic between racks in HDFS by optimizing block distribution. The SI‐CLS algorithm calculates a fitness value for each block, aiming to increase data availability and reduce latency. Performance metrics, including latency, data availability, and load balancing, indicate the effectiveness of SI‐CLS. Adopting this algorithm enhances HDFS performance, ensuring better data availability and lower latency, resulting in improved system reliability.

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Cost-effective clonal selection and AIS-based load balancing in cloud computing environment

Mosayebi,

Azmi

2024

J Supercomput

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Enhancing data security using global mutation based novel artificial immune network optimization in public cloud storage system

Cited by 4 publications

References 43 publications

Improved secure dynamic bit standard technique for a private cloud platform to address security challenges

Improved secure dynamic bit standard technique for a private cloud platform to address security challenges

Swarm Intelligence with a Chaotic Leader and a Salp algorithm: HDFS optimization for reduced latency and enhanced availability

Cost-effective clonal selection and AIS-based load balancing in cloud computing environment

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