Data security and privacy in wireless body area networks

By Ming Li, Wenjing Lou, Kui Ren. IEEE wireless communications, 2010

643 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering

View Paper: https://www.semanticscholar.org/paper/c16b8b3d65c8d49bbd7c4de0876186edf793fc2b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Kui Ren
2. Wenjing Lou
3. Ming Li
4. Ning Cao
5. Shucheng Yu
6. Xuemin Shen
7. Xiaodong Lin
8. Rongxing Lu

In Biomedical Engineering

1. Shucheng Yu
2. Wenjing Lou
3. Ming Li
4. Shahaboddin Shamshirband

Citations in the corpus

• Survey of main challenges (security and privacy) in wireless body area networks for healthcare applications (2017, background): “For instance, an adversary may capture the data from the wireless channels and modify the results [14,15].”
• Smart community: an internet of things application (2011, background): “As a result, there is no or very little associated monetary cost.”
• Sybil Attacks and Their Defenses in the Internet of Things (2014, background): “Thus, a large volume of embedded sensors are deployed in the target area to monitor the environmental conditions or human biologic information [33].”
• Wearable Sensors for Human Activity Monitoring: A Review (2015, neutral): “medical response systems [51].”
• Authorized Private Keyword Search over Encrypted Data in Cloud Computing (2011, background): “To cope with the tough trust issues and to ensure owners’ control over their own privacy, applying data encryption on the documents before outsourcing has been proposed as a promising solution, which is already adopted by many recent works [26], [7], [24].”
• Securing Personal Health Records in Cloud Computing: Patient-Centric and Fine-Grained Data Access Control in Multi-owner Settings (2010, methodology): “To avoid such inconveniences, novel one-to-many encryption methods such as attribute-based encryption can be used [15].”
• Scalable and Secure Sharing of Personal Health Records in Cloud Computing Using Attribute-Based Encryption (2019, neutral): “The main advantage of their solution is, each user can obtain secret keys from any subset of the TAs in the system, in contrast to the CC MA-ABE.”
• Differential Privacy Techniques for Cyber Physical Systems: A Survey (2018, background): “However, if one does not uses a strong privacy preservation scheme during this communication, then any adversary can try to hack this personal information and can use it for illegal benefits such as blackmailing, false information injection, etc [8].”