Cloud computing and cyber security : a secure crypto-based data outsourcing and sensitive data monitoring in cloud / A.S. Kalyan Kumar, T. Abdul Razak
Material type:
TextPublisher: New Delhi : Adhyyan Books , 2022Description: 163 pages ; illustrations ; 23 cmISBN: 978-8195995950Subject(s): Cloud computingDDC classification: 004 Summary: The aim of this book is to meet the brief objective, several sub-objectives are often developed to reinforce the info security and privacy in cloud computing such as (i) to develop a lightweight model for data anonymization and unlikability when data is outsourced to the cloud. () To develop a method using an appropriate encryption algorithm to secure the privacy of sensitive data in the cloud. (iii) To validate the proposed model and the method for security and privacy of data outsourcing in the cloud with recent benchmarks.
The security and privacy may be enhanced by encrypting the user data before sending it to the server in the cloud. The present methodologies have few challenges in terms of security, execution time, forced to take care of an equivalent length of the key and therefore the plain text, more computational cost, and inadequate key generation.
The research provides data anonymity and unlikability to a foreign cloud server, and hence Secure Crypto-based Data Outsourcing Model (SCDOM) has been proposed. For encryption and decryption, the Blowfish technique is used. The Message Authentication Code (MAC) is generated for security, and it avoids the usage of complicated cryptographic key certificates.
The lightweight models are inclined to mitigate the computation complexity, time, and cost. During encryption, 5 keys are generated to enhance privacy. While applying the 1st key, if any unauthorized attack occurs then this key can be rejected and the next key can be considered for verification. The encryption and decryption are done by using the Honeybee algorithm. The proposed methodology mainly stimulates potential security against intruders. It maintains parallelism between the key and length of plain text and mainly mitigates the computational cost and execution time.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| Books | Institute of Public Enterprise, Library S Campus | 004 KAL (Browse shelf) | Available | 47810 |
The aim of this book is to meet the brief objective, several sub-objectives are often developed to reinforce the info security and privacy in cloud computing such as (i) to develop a lightweight model for data anonymization and unlikability when data is outsourced to the cloud. () To develop a method using an appropriate encryption algorithm to secure the privacy of sensitive data in the cloud. (iii) To validate the proposed model and the method for security and privacy of data outsourcing in the cloud with recent benchmarks.
The security and privacy may be enhanced by encrypting the user data before sending it to the server in the cloud. The present methodologies have few challenges in terms of security, execution time, forced to take care of an equivalent length of the key and therefore the plain text, more computational cost, and inadequate key generation.
The research provides data anonymity and unlikability to a foreign cloud server, and hence Secure Crypto-based Data Outsourcing Model (SCDOM) has been proposed. For encryption and decryption, the Blowfish technique is used. The Message Authentication Code (MAC) is generated for security, and it avoids the usage of complicated cryptographic key certificates.
The lightweight models are inclined to mitigate the computation complexity, time, and cost. During encryption, 5 keys are generated to enhance privacy. While applying the 1st key, if any unauthorized attack occurs then this key can be rejected and the next key can be considered for verification. The encryption and decryption are done by using the Honeybee algorithm. The proposed methodology mainly stimulates potential security against intruders. It maintains parallelism between the key and length of plain text and mainly mitigates the computational cost and execution time.
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