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Achieving Efficient and Secure Data Acquisition for Cloud-supported Internet of Things in Smart Grid (1810.10746v1)

Published 25 Oct 2018 in cs.CR

Abstract: Cloud-supported Internet of Things (Cloud-IoT) has been broadly deployed in smart grid systems. The IoT front-ends are responsible for data acquisition and status supervision, while the substantial amount of data is stored and managed in the cloud server. Achieving data security and system efficiency in the data acquisition and transmission process are of great significance and challenging, because the power grid-related data is sensitive and in huge amount. In this paper, we present an efficient and secure data acquisition scheme based on CP-ABE (Ciphertext Policy Attribute Based Encryption). Data acquired from the terminals will be partitioned into blocks and encrypted with its corresponding access sub-tree in sequence, thereby the data encryption and data transmission can be processed in parallel. Furthermore, we protect the information about the access tree with threshold secret sharing method, which can preserve the data privacy and integrity from users with the unauthorized sets of attributes. The formal analysis demonstrates that the proposed scheme can fulfill the security requirements of the Cloud-supported IoT in smart grid. The numerical analysis and experimental results indicate that our scheme can effectively reduce the time cost compared with other popular approaches.

Citations (205)

Summary

  • The paper presents a scheme for secure and efficient data acquisition in smart grid Cloud-IoT systems using parallel CP-ABE and parallel data processing.
  • Performance evaluations show the scheme significantly reduces encryption and decryption time while maintaining robust security comparable to traditional CP-ABE.
  • The findings have implications for enhancing data management security, throughput, and scalability in smart grid IoT and potentially other complex IoT environments.

Efficient and Secure Data Acquisition for Cloud-Supported IoT in Smart Grid

The paper presents an advanced scheme to improve data acquisition efficiency and security in Cloud-supported Internet of Things (Cloud-IoT) systems specifically implemented in smart grid networks. By integrating Ciphertext Policy Attribute Based Encryption (CP-ABE) with strategic data partitioning and parallel encryption, it addresses significant challenges related to data handling in these complex systems, particularly concerning enormous and sensitive data volumes typical for power grids.

Key Contributions and Methodologies

The paper introduces a parallel data processing method that enables data acquired from IoT terminals to be split into blocks. Each block is encrypted and transmitted simultaneously, independent of the others. This parallelization in both data encryption and transmission processes substantially reduces system response time and user waiting time, outperforming conventional methods reliant on serial operations.

Furthermore, the dual secret sharing scheme applied in this work enhances security by protecting data access tree information. This approach guarantees that data is only accessible to users whose attributes satisfy a predetermined access policy. Through this method, data privacy and integrity are rigorously maintained against unauthorized access attempts.

Performance Evaluation

The authors provide thorough security analysis and performance evaluation to demonstrate the robustness and efficiency of their proposed scheme. Formal analysis confirms that the security level is on par with traditional CP-ABE frameworks. Numerical analysis and experimental results further reveal that the proposed method significantly diminishes encryption and decryption time, showcasing a notable performance gain over conventional CP-ABE approaches.

The experimental setup validated the substantial reduction in time for encryption and transmission by concurrently encrypting multiple data blocks, each with its respective sub-tree policy in the access control structure. Comparisons with existing methods highlight the enhanced efficiency and scalability of the presented scheme, making it highly applicable in practical smart grid environments.

Implications and Future Work

The findings from this paper hold vital implications for both theoretical advancements and practical implementations in IoT-backed smart grids. The utilization of CP-ABE with parallel encryption schemes and dual secret sharing frameworks could potentially transform how data is managed in complex IoT environments, ensuring not only heightened security but also improved system throughput and scalability.

Future research may explore the real-time applicability of such data acquisition strategies, emphasizing not just offline data security, but also integrating timeliness and immediacy into the encryption and decryption processes. Additionally, extending these methodologies to other IoT-supported infrastructures could foster further advancements in data security paradigms essential for modern digital ecosystems.

Conclusion

In summary, the paper advances a compelling framework for secure and efficient data acquisition within Cloud-IoT systems in smart grids. By judiciously applying CP-ABE and innovative data processing techniques, it lays a rigorous foundation for future explorations into optimized data handling in IoT-enriched environments, addressing both current security concerns and operational efficiency challenges.