Security Properties of Gait for Mobile Device Pairing
April 11, 2018 Β· Declared Dead Β· π IEEE Transactions on Mobile Computing
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Arne BrΓΌsch, Ngu Nguyen, Dominik SchΓΌrmann, Stephan Sigg, Lars Wolf
arXiv ID
1804.03997
Category
cs.CR: Cryptography & Security
Cross-listed
cs.HC
Citations
36
Venue
IEEE Transactions on Mobile Computing
Last Checked
6 months ago
Abstract
Gait has been proposed as a feature for mobile device pairing across arbitrary positions on the human body. Results indicate that the correlation in gait-based features across different body locations is sufficient to establish secure device pairing. However, the population size of the studies is limited and powerful attackers with e.g. capability of video recording are not considered. We present a concise discussion of security properties of gait-based pairing schemes including a discussion of popular quantization schemes, classification and analysis of attack surfaces, discussion of statistical properties of generated sequences, an entropy analysis, as well as possible threats and security weaknesses of gait-based pairing systems. For one of the schemes considered, we present modifications to fix an identified security flaw. As a general limitation of gait-based authentication or pairing systems, we further demonstrate that an adversary with video support can create key sequences that are sufficiently close to on-body generated acceleration sequences to breach gait-based security mechanisms.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Cryptography & Security
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
The Limitations of Deep Learning in Adversarial Settings
R.I.P.
π»
Ghosted
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
R.I.P.
π»
Ghosted
Spectre Attacks: Exploiting Speculative Execution
R.I.P.
π»
Ghosted
How To Backdoor Federated Learning
R.I.P.
π»
Ghosted
Evasion Attacks against Machine Learning at Test Time
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted