Radio-telepathy: extracting a secret key from an unauthenticated wireless channel

By Suhas Mathur, Wade Trappe, Narayan B. Mandayam, Chunxuan Ye, Alex Reznik. ACM/IEEE International Conference on Mobile Computing and Networking, 2008

796 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/9e18e18bd79bd53a0986cff743ea4bada88b472d

How researchers see this paper

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

In Computer Networks and Communications

1. Xianbin Wang
2. Lajos Hanzo
3. Jia Zhu
4. Yulong Zou
5. Huseyin Arslan
6. Yunhao Liu
7. Zheng Yang
8. David F. Kotz

In Computer Vision and Pattern Recognition

1. Huseyin Arslan
2. David F. Kotz
3. Haji. M. Furqan
4. Fei Sha
5. Alex Reznik
6. Narayan B. Mandayam
7. Wade Trappe
8. Lajos Hanzo

In Electrical and Electronic Engineering

1. Zheng Yang
2. Yunhao Liu
3. Zimu Zhou
4. Xianbin Wang
5. Huseyin Arslan
6. Lajos Hanzo
7. Jia Zhu
8. Yulong Zou

Citations in the corpus

• A Survey on Wireless Security: Technical Challenges, Recent Advances, and Future Trends (2015, methodology): “To this end, a RSS based secret key extraction algorithm was proposed in [149] by exploitin g RSS measurements of the main channel in order to generate secret bits for an IEEE 802.”
• From RSSI to CSI (2013, methodology): “[Mathur et al. 2008] proposed a key extraction scheme from unauthenticated wireless channel via the amplitudes of CIR.”
• Privacy in mobile technology for personal healthcare (2012, methodology): “Another RF-based approach uses physical properties of the wireless channel between two nodes to derive key material [Mathur et al. 2008; Jana et al. 2009]; since the wireless channel fades quickly with distance, they show that an eavesdropping adversary cannot obtain the key, nor can an active adver”
• Information-Theoretically Secret Key Generation for Fading Wireless Channels (2009, methodology): “the parameters chosen for the level crossing algorithm, the bits extracted by Alice and Bob are statistically random and have high-entropy per bit. This has been tested for and previously reported in [38] using a suite of statistical randomness tests provided by NIST [3]. III. QUANTIZATION-BASED SEC”
• Classifications and Applications of Physical Layer Security Techniques for Confidentiality: A Comprehensive Survey (2019, methodology): “[179] extracted secret bits from RSSI and CIR measurements by using two-level crossing excursion-based quantization.”
• Cloud-enabled privacy-preserving collaborative learning for mobile sensing (2012, background): “These popular classifiers are used often in the mobile sensing literature for logical localization [ 7], collaborative video sensing [8], behavioral detection of malware [ 10], device identification [40] and so on.”