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

Rajendra Kumar Dwivedi, Rakesh Kumar, R. Buyya
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引用次数: 6

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.
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使用基于属性的椭圆曲线加密保护医疗监控传感器云
在许多物联网(IoT)应用中,传感器网络与云集成以获得各种好处。医疗监测传感器云是将可穿戴传感器生成的患者健康数据存储在云上,方便授权医生远程监测和建议的应用程序之一。病人在云端的数据必须是安全的。现有的安全方案(例如,基于密钥策略属性的加密[KP-ABE]和基于密文策略属性的加密[CP-ABE])具有更高的计算开销。本文提出了一种基于属性的椭圆曲线加密(ABECC)安全机制,以保证数据完整性、数据机密性和细粒度访问控制。它还减少了计算开销。ABECC是在。net框架中实现的。在ABECC中使用椭圆曲线加密(ECC),减少了密钥长度,从而提高了加密、解密和密钥生成时间。ABECC分别比现有的KP-ABE和CP-ABE方法快1.7倍和1.4倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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