Mobile Device Fingerprinting Recognition using Insensitive Information

Wei, Dujia; Gu, Yu; Du, Yong

doi:10.1109/icicml57342.2022.10009697

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…To be considered valid, the authors Wei, Gu & Du (2022) argue that a unique identifier should meet the following requirements: have high entropy, so the fingerprint could be immediately associated with the device, to be persistent over time, and to be resilient to forgery. Also, it should be easy to integrate into a given architecture, facilitating connectivity and interoperability between solutions.…”

Section: Related Workmentioning

confidence: 99%

A Multi-layer Approach for Mobile Devices: Behavioral Fingerprinting

Apostol¹,

Mocanu²,

Mocanu³

et al. 2023

SIC

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In distributed systems such as mobile networks, problems like heterogeneity and real-time reliable responses represent constant challenges. Furthermore, reliable identification of the participants in mobile networks is a challenging research problem because of the susceptibility to security attacks. Also, reliable identification of participants means to be able to distinguish between the device and its user. In this paper, a multi-layer mechanism is proposed for reliable identification of devices and their users in mobile networks, based on the smartphone sensor data. The proposed model can uniquely identify both the device and the users by leveraging a mobile application that harvests mobile sensor data in various usage scenarios and analyse different usage patterns. Moreover, in order to achieve data confidentiality, a cryptographic scheme is integrated, based on the public key exchange mechanism. The obtained results show that the model proposed in this paper provides meaningful insights about user behavioral patterns, without special permissions and without disclosing the actual owner identity or biometric data.

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Section: Related Workmentioning

confidence: 99%