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An improved finegrained ciphertext policy based temporary keyword search on encrypted data for secure cloud storage.

Mamta Dabra1, Shivani Sharma2, Sachin Kumar3

  • 1Department of Computer Science and Engineering, Punjab Engineering College, Chandigarh, India.

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This study introduces a secure temporary keyword search for cloud-based health data, preventing privacy breaches from search tokens. The novel method enhances data security by limiting access to specific time intervals, mitigating insider threats.

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Area of Science:

  • Computer Science
  • Information Security
  • Healthcare Informatics

Background:

  • Cloud environments require robust security for sensitive health data.
  • Existing attribute-based keyword search methods pose privacy risks via search tokens.
  • Unauthorized access and insider threats are significant concerns in healthcare data management.

Purpose of the Study:

  • To develop a secure temporary keyword search mechanism for confidential health data in the cloud.
  • To prevent privacy violations associated with traditional search tokens.
  • To mitigate insider threats in healthcare by restricting data access temporally.

Main Methods:

  • Proposed a novel ciphertext policy fine-grained temporary keyword search scheme.
  • Implemented security measures to prevent misuse of search tokens.
  • Conducted formal security proofs against Selectively Chosen Keyword Attacks in the generic bilinear group model.

Main Results:

  • The proposed scheme effectively prevents privacy threats from search tokens.
  • Demonstrated linear complexity of the encryption algorithm concerning the number of attributes.
  • Formal security proofs confirm the scheme's robustness against specific attacks.

Conclusions:

  • The novel temporary keyword search scheme enhances security for cloud-based health data.
  • The approach mitigates insider threats by limiting data access windows.
  • The scheme offers a practical and secure solution for sensitive data management in healthcare.