MASK-BAN: Movement-aided authenticated secret key extraction utilizing channel characteristics in body area networks

Lu Shi, Jiawei Yuan, Shucheng Yu, Ming Li

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


Recently, most wireless network security schemes merely based on physical layer characteristics tackle the two fundamental issues-device authentication and secret key extraction separately. It remains an open problem to simultaneously achieve device authentication and fast secret key extraction merely using wireless physical layer characteristics, without the help of advanced hardware or out-of-band channel. In this paper, we answer this open problem in the setting of wireless body area networks (BANs). We propose MASK-BAN, a lightweight fast authenticated secret key extraction scheme for intra-BAN communication. Our scheme neither introduces advanced hardware nor relies on out-of-band channels. To perform device authentication and fast secret key extraction at the same time, we exploit the heterogeneous channel characteristics among the collection of on-body channels during body motion. On one hand, MASK-BAN achieves authentication through multihop stable channels, which greatly reduces the false positive rate as compared to existing work. On the other hand, based on dynamic channels, key extraction between two on-body devices with multihop relay nodes is modeled as a max-flow problem, and a novel collaborative secret key generation algorithm is introduced to maximize the key generation rate. Extensive real-world experiments on low-end commercial-off-the-shelf sensor devices validate MASK-BAN's great authentication capability and high-secret key generation rate.

Original languageEnglish (US)
Article number7006641
Pages (from-to)52-62
Number of pages11
JournalIEEE Internet of Things Journal
Issue number1
StatePublished - Feb 1 2015
Externally publishedYes


  • Authenticated key generation
  • physical layer
  • received signal strength (RSS)
  • sensor
  • wireless body area network (WBAN).

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


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