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By: Mansi Ahirwar and Manoj Tyagi.
1-Student, Department of Computer Science and Engineering, Technocrats Institute of Technology, Anandnagar, Bhopal
2-Professor, Department of Computer Science and Engineering, Technocrats Institute of Technology, Anandnagar, Bhopal
This generation of cloud computing has characterized the Internet of Things with exponentially increasing data generation, processing, and storage. Regrettably, however, accompanying this trend of growth is the increased concern for cloud-based systems about security, privacy, and control of access to data. The proposed work introduces a hybrid cryptographic framework that combines AES, OTP, and RSA encryption methods with temporal mechanisms to enhance the security of data in the cloud. This framework benefits from both symmetric and asymmetric approaches to encryption; hence, the reliability for secure transfer, confidentiality, and efficient key management is enhanced. OTP integration will include security from brute force attacks and unauthenticated access into the application. Temporal security is added through time-bound implementation of access control mechanisms: access to data will be matched to the time intervals as the overall robustness of dynamic clouds over time. Side-channel attacks and defense: “The paper presents an overview of the application of hybrid deep learning models for countering side-channel attacks, showing potential towards better accuracy in key prediction.” Although the proposed hybrid cryptographic model has drawbacks such as no scalability, insecure APIs, or data breaches, it is scalable, adaptive, and efficient in dealing with issues concerning cloud data security. Refinement of these hybrid models to deal with emerging threats and optimization of their performance in large-scale clouds may be some future research directions.
Keywords: Cloud computing, hybrid cryptography, AES, OTP, RSA, temporal access control, data security, IoT, asymmetric encryption, symmetric encryption, side-channel attacks.
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Citation:
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