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Secure Healthcare Monitoring Sensor Cloud With Attribute-Based Elliptical Curve Cryptography

Author

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  • Rajendra Kumar Dwivedi

    (Madan Mohan Malaviya University of Technology, Gorakhpur, India)

  • Rakesh Kumar

    (Madan Mohan Malaviya University of Technology, Gorakhpur, India)

  • Rajkumar Buyya

    (The University of Melbourne, Melbourne, Australia)

Abstract

Sensor networks are integrated with cloud in many internet of things (IoT) applications for various benefits. Healthcare monitoring sensor cloud is one of the application that allows storing the patients' health data generated by their wearable sensors at cloud and facilitates the authorized doctors to monitor and advise them remotely. Patients' data at cloud must be secure. Existing security schemes (e.g., key policy attribute-based encryption [KP-ABE] and ciphertext policy attribute-based encryption [CP-ABE]) have higher computational overheads. In this paper, a security mechanism called attribute-based elliptical curve cryptography (ABECC) is proposed that guarantees data integrity, data confidentiality, and fine-grained access control. It also reduces the computational overheads. ABECC is implemented in .NET framework. Use of elliptical curve cryptography (ECC) in ABECC reduces the key length, thereby improving the encryption, decryption, and key generation time. It is observed that ABECC is 1.7 and 1.4 times faster than the existing approaches of KP-ABE and CP-ABE, respectively.

Suggested Citation

  • Rajendra Kumar Dwivedi & Rakesh Kumar & Rajkumar Buyya, 2021. "Secure Healthcare Monitoring Sensor Cloud With Attribute-Based Elliptical Curve Cryptography," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 11(3), pages 1-18, July.
    • Handle: RePEc:igg:jcac00:v:11:y:2021:i:3:p:1-18
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    Cited by:

    1. Gupta, Brij B. & Gaurav, Akshat & Kumar Panigrahi, Prabin, 2023. "Analysis of security and privacy issues of information management of big data in B2B based healthcare systems," Journal of Business Research, Elsevier, vol. 162(C).

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