Security and Privacy in Smart Health: Efficient Policy-Hiding Attribute-Based Access Control

Zhang, Yinghui; Zheng, Dong; Deng, Robert H.

doi:10.1109/jiot.2018.2825289

Cited by 398 publications

(228 citation statements)

References 53 publications

Supporting

Mentioning

221

Contrasting

Order By: Relevance

“…Although it does not consider access control, it shows the benefits of ABAC in IoT. Zhang et al use ABAC to code privacy rules for health applications . It encompasses the storage, use, and access of sensitive patient information.…”

Section: Related Workmentioning

confidence: 99%

CASA‐IoT: Scalable and context‐aware IoT access control supporting multiple users

et al. 2019

View full text Add to dashboard Cite

Summary The Internet of Things (IoT) supports many users and context‐aware applications controlling heterogeneous IoT devices. This differs from traditional networks, in which a single entity manages each device. Thus, new access control models must be created in order to support more responsive, scalable, secure, and autonomous management. This article presents an attribute‐based access control model, which applies conflict resolution and access delegation in a multiuser and multiapplication environment. With scalability in mind, we propose the caching of access permissions, as well as a split policy processing model in which the devices with enough computational power perform part of the processing. The proposed model was implemented as part of the ManIoT architecture an d evaluated in experiments on a testbed to demonstrate its efficiency. Results show that our model accelerates the processing of access management policies from 51% by up to 79%.

show abstract

Section: Related Workmentioning

confidence: 99%

CASA‐IoT: Scalable and context‐aware IoT access control supporting multiple users

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Setup algorithm, Encryption algorithm, Generate token algorithm, Check algorithm. [17] In this paper the flaws of traditional CP-ABE like revealing the confidential information have been overcome using PASH a privacy aware s-health access control system. In PASH the attribute values which are more sensitive are kept hidden in encrypted SHR and only attribute names are revealed through which it attains security in standard model.…”

Section: IImentioning

confidence: 99%

Protected Entree Design for Big Data Knowledge in Cloud

Sudha¹

2019

IJRASET

View full text Add to dashboard Cite

Nowadays, the access to the data in the cloud is provided with weak authentication, of the user. Besides, as more and organizations are using clouds to store their data, it becomes more challenging to deal with the issue of access policy. Due to this the leakage of critical information are not well handled. Integrity and confidentiality of the personal information are questioned and are not secure. To overcome this, we propose a new NTRU decryption procedure to overcome the decryption failures of the original NTRU without reducing the security strength of NTRU. The scheme can verify user's access legitimacy and validate the information provided by other users for correct plaintext recovery. We devise an efficient and verifiable method to update the cryptosystem stored in clouds without increasing any risk when the access policy is dynamically changed.

show abstract

“…Compared with the traditionally fixed deployment sensing mode, the cloud-based mobile crowdsourcing has proven to be an attractive solution to provide data storage and share services for resource-limited mobile devices in a privacy preserving manner [3]. Mobile crowdsensing has been widely applied to environmental monitoring [4], intelligent traffic systems [5], social behavior analyses [6,7], urban management [6], public security [8] and other fields with the advantages of low deployment costs, simple maintenance, and excellent scalability.…”

Section: Introductionmentioning

confidence: 99%

Achieving Incentive, Security, and Scalable Privacy Protection in Mobile Crowdsensing Services

Xiong

Chen

et al. 2018

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Mobile crowdsensing as a novel service schema of the Internet of Things (IoT) provides an innovative way to implement ubiquitous social sensing. How to establish an effective mechanism to improve the participation of sensing users and the authenticity of sensing data, protect the users' data privacy, and prevent malicious users from providing false data are among the urgent problems in mobile crowdsensing services in IoT. These issues raise a gargantuan challenge hindering the further development of mobile crowdsensing. In order to tackle the above issues, in this paper, we propose a reliable hybrid incentive mechanism for enhancing crowdsensing participations by encouraging and stimulating sensing users with both reputation and service returns in mobile crowdsensing tasks. Moreover, we propose a privacy preserving data aggregation scheme, where the mediator and/or sensing users may not be fully trusted. In this scheme, differential privacy mechanism is utilized through allowing different sensing users to add noise data, then employing homomorphic encryption for protecting the sensing data, and finally uploading ciphertext to the mediator, who is able to obtain the collection of ciphertext of the sensing data without actual decryption. Even in the case of partial sensing data leakage, differential privacy mechanism can still ensure the security of the sensing user's privacy. Finally, we introduce a novel secure multiparty auction mechanism based on the auction game theory and secure multiparty computation, which effectively solves the problem of prisoners' dilemma incurred in the sensing data transaction between the service provider and mediator. Security analysis and performance evaluation demonstrate that the proposed scheme is secure and efficient.

show abstract

Security and Privacy in Smart Health: Efficient Policy-Hiding Attribute-Based Access Control

Cited by 398 publications

References 53 publications

CASA‐IoT: Scalable and context‐aware IoT access control supporting multiple users

CASA‐IoT: Scalable and context‐aware IoT access control supporting multiple users

Protected Entree Design for Big Data Knowledge in Cloud

Achieving Incentive, Security, and Scalable Privacy Protection in Mobile Crowdsensing Services

Contact Info

Product

Resources

About