Anonymous Anti-Sybil Attack Protocol for Mobile Healthcare Networks Analytics
Title | Anonymous Anti-Sybil Attack Protocol for Mobile Healthcare Networks Analytics |
Publication Type | Conference Paper |
Year of Publication | 2017 |
Authors | Zhang, P., Zhang, X., Sun, X., Liu, J. K., Yu, J., Jiang, Z. L. |
Conference Name | 2017 IEEE Trustcom/BigDataSE/ICESS |
Keywords | ABS, anonymous anti-sybil attack protocol, attribute-based signature, composability, Data analysis, data privacy, digital signatures, disease diagnosis, disease treatment, Fiat-Shamir framework, fine-grained authentication scheme, Health Care, health services, identity privacy, lattice assumption, medical histories, medical information systems, Metrics, MHN, mobile computing, mobile healthcare networks analytics, patient diagnosis, patient treatment, patients health data, pubcrawl, Resiliency, sybil attacks, wearable devices |
Abstract | Mobile Healthcare Networks (MHN) continuouslycollect the patients' health data sensed by wearable devices, andanalyze the collected data pre-processed by servers combinedwith medical histories, such that disease diagnosis and treatmentare improved, and the heavy burden on the existing healthservices is released. However, the network is vulnerable to Sybilattacks, which would degrade network performance, disruptproceedings, manipulate data or cheat others maliciously. What'smore, the user is reluctant to leak identity privacy, so the identityprivacy preserving makes Sybil defenses more difficult. One ofthe best choices is mutually authenticating each other with noidentity information involved. Thus, we propose a fine-grainedauthentication scheme based on Attribute-Based Signature (ABS)using lattice assumption, where a signer is authorized by an at-tribute set instead of single identity string. This ABS scheme usesFiat-Shamir framework and supports flexible threshold signaturepredicates. Moreover, to anonymously guarantee integrity andavailability of health data in MHN, we design an anonymousanti-Sybil attack protocol based on our ABS scheme, so thatSybil attacks are prevented. As there is no linkability betweenidentities and services, the users' identity privacy is protected. Finally, we have analyzed the security and simulated the runningtime for our proposed ABS scheme. |
URL | https://ieeexplore.ieee.org/document/8029501/ |
DOI | 10.1109/Trustcom/BigDataSE/ICESS.2017.298 |
Citation Key | zhang_anonymous_2017 |
- lattice assumption
- Wearable devices
- sybil attacks
- Resiliency
- pubcrawl
- patients health data
- patient treatment
- patient diagnosis
- mobile healthcare networks analytics
- mobile computing
- MHN
- Metrics
- medical information systems
- medical histories
- ABS
- identity privacy
- health services
- health care
- fine-grained authentication scheme
- Fiat-Shamir framework
- disease treatment
- disease diagnosis
- digital signatures
- data privacy
- data analysis
- composability
- attribute-based signature
- anonymous anti-sybil attack protocol