SCR-Auth: Secure Call Receiver Authentication on Smartphones Using Outer Ear Echoes
- URL: http://arxiv.org/abs/2404.15000v2
- Date: Fri, 10 Jan 2025 14:47:13 GMT
- Title: SCR-Auth: Secure Call Receiver Authentication on Smartphones Using Outer Ear Echoes
- Authors: Xiping Sun, Jing Chen, Kun He, Zhixiang He, Ruiying Du, Yebo Feng, Qingchuan Zhao, Cong Wu,
- Abstract summary: We propose SCR-Auth, a secure call receiver authentication scheme for smartphones.
It sends inaudible acoustic signals through the earpiece speaker to actively sense the call receiver's outer ear structure.
Results show an average balanced accuracy of 96.95% and resilience against potential attacks.
- Score: 14.78387043362623
- License:
- Abstract: Receiving calls is one of the most universal functions of smartphones, involving sensitive information and critical operations. Unfortunately, to prioritize convenience, the current call receiving process bypasses smartphone authentication mechanisms (e.g., passwords, fingerprint recognition, and face recognition), leaving a significant security gap. To address this issue, we propose SCR-Auth, a secure call receiver authentication scheme for smartphones that leverages outer ear echoes. It sends inaudible acoustic signals through the earpiece speaker to actively sense the call receiver's outer ear structure and records the resulting echoes using the top microphone. These echoes are then analyzed to extract unique outer ear biometric information for authentication. It operates implicitly, without requiring extra hardware or imposing additional burden. Comprehensive experiments conducted under diverse conditions demonstrate SCR-Auth's effectiveness and security, showing an average balanced accuracy of 96.95% and resilience against potential attacks.
Related papers
- Preventing Radio Fingerprinting through Friendly Jamming [5.074726108522963]
Radio frequency fingerprinting enables a passive receiver to recognize and authenticate a transmitter without the need for cryptographic tools.
We examine the hostile usage of radio frequency fingerprinting, which facilitates the unauthorized tracking of wireless devices in the field by malicious entities.
We suggest a method to sanitize the transmitted signal of its fingerprint using a jammer, deployed on purpose to improve devices' anonymity on the channel.
arXiv Detail & Related papers (2024-07-11T09:01:46Z) - Eve Said Yes: AirBone Authentication for Head-Wearable Smart Voice Assistant [10.694874051404648]
Air and bone conduction (AC/BC) from the same vocalization are coupled (or concurrent) and user-level unique.
The legitimate user can defeat acoustic domain and even cross-domain spoofing samples with the proposed two-stage AirBone authentication.
arXiv Detail & Related papers (2023-09-26T19:03:45Z) - Locally Authenticated Privacy-preserving Voice Input [10.82818142802482]
Service providers must authenticate their users, although individuals may wish to maintain privacy.
Preserving privacy while performing authentication is challenging, particularly where adversaries can use biometric data to train transformation tools.
We introduce a secure, flexible privacy-preserving system to capture and store an on-device fingerprint of the users' raw signals.
arXiv Detail & Related papers (2022-05-27T14:56:01Z) - Spotting adversarial samples for speaker verification by neural vocoders [102.1486475058963]
We adopt neural vocoders to spot adversarial samples for automatic speaker verification (ASV)
We find that the difference between the ASV scores for the original and re-synthesize audio is a good indicator for discrimination between genuine and adversarial samples.
Our codes will be made open-source for future works to do comparison.
arXiv Detail & Related papers (2021-07-01T08:58:16Z) - Multimodal Personal Ear Authentication Using Smartphones [0.0]
fingerprint authentication cannot be used when hands are wet, and face recognition cannot be used when a person is wearing a mask.
We examine a personal authentication system using the pinna as a new approach for biometric authentication on smartphones.
arXiv Detail & Related papers (2021-03-23T14:19:15Z) - Aurora Guard: Reliable Face Anti-Spoofing via Mobile Lighting System [103.5604680001633]
Anti-spoofing against high-resolution rendering replay of paper photos or digital videos remains an open problem.
We propose a simple yet effective face anti-spoofing system, termed Aurora Guard (AG)
arXiv Detail & Related papers (2021-02-01T09:17:18Z) - Speech Enhancement for Wake-Up-Word detection in Voice Assistants [60.103753056973815]
Keywords spotting and in particular Wake-Up-Word (WUW) detection is a very important task for voice assistants.
This paper proposes a Speech Enhancement model adapted to the task of WUW detection.
It aims at increasing the recognition rate and reducing the false alarms in the presence of these types of noises.
arXiv Detail & Related papers (2021-01-29T18:44:05Z) - Stay Connected, Leave no Trace: Enhancing Security and Privacy in WiFi
via Obfuscating Radiometric Fingerprints [8.89054576694426]
The intrinsic hardware imperfection of WiFi chipsets manifests itself in the transmitted signal, leading to a unique radiometric fingerprint.
Recent works propose practical fingerprinting solutions that can be readily implemented in commercial-off-the-shelf devices.
We show analytically and experimentally that these solutions are highly vulnerable to impersonation attacks.
We propose RF-Veil, a radiometric fingerprinting solution that not only is robust against impersonation attacks but also protects user privacy.
arXiv Detail & Related papers (2020-11-25T11:10:59Z) - Open-set Adversarial Defense [93.25058425356694]
We show that open-set recognition systems are vulnerable to adversarial attacks.
Motivated by this observation, we emphasize the need of an Open-Set Adrial Defense (OSAD) mechanism.
This paper proposes an Open-Set Defense Network (OSDN) as a solution to the OSAD problem.
arXiv Detail & Related papers (2020-09-02T04:35:33Z) - Decentralized Privacy-Preserving Proximity Tracing [50.27258414960402]
DP3T provides a technological foundation to help slow the spread of SARS-CoV-2.
System aims to minimise privacy and security risks for individuals and communities.
arXiv Detail & Related papers (2020-05-25T12:32:02Z) - Multi-task self-supervised learning for Robust Speech Recognition [75.11748484288229]
This paper proposes PASE+, an improved version of PASE for robust speech recognition in noisy and reverberant environments.
We employ an online speech distortion module, that contaminates the input signals with a variety of random disturbances.
We then propose a revised encoder that better learns short- and long-term speech dynamics with an efficient combination of recurrent and convolutional networks.
arXiv Detail & Related papers (2020-01-25T00:24:45Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.