Corpus ID: 10543406

Hacking Mobile Phones Using 2 D Printed Fingerprints

@inproceedings{Cao2016HackingMP,
  title={Hacking Mobile Phones Using 2 D Printed Fingerprints},
  author={Kai Cao and Anil K. Jain},
  year={2016}
}
Fingerprint is the most popular biometric trait due to the perceived uniqueness and persistence of friction ridge pattern on human fingers [1]. Following the introduction of iPhone 5S with Touch ID fingerprint sensor in September 2013, most of the mobile phones, such as iPhone 5s/6/6+, Samsung Galaxy S5/S6, HTC One Max, Huawei Honor 7, Meizu MX4 Pro and others, now come with embedded fingerprint sensors for phone unlock. It has been forecasted that 50% of smartphones sold by 2019 will have an… Expand

Figures from this paper

Attack Potential Evaluation in Desktop and Smartphone Fingerprint Sensors: Can They Be Attacked by Anyone?
TLDR
This paper evaluated 4 desktop fingerprint sensors of different technologies by attacking them with 7 different fake finger materials, and gathered 15 simulated attackers with no background in biometrics to create fake fingers of several materials. Expand
POSTER: Rethinking Fingerprint Identification on Smartphones
TLDR
A fake fingerprint attack is developed that exploits the latent fingerprints as actual risk, and a fake fingerprint image is reconstructed in good quality for small touch sensors for fingerprint identification of a user. Expand
Attacking a Smartphone Biometric Fingerprint System: A Novice's Approach
TLDR
This study explores how easy it is to successfully attack a fingerprint system using a fake finger manufactured from commonly available materials and the material combinations that lead to these attacks. Expand
Bypass Biometric Lock Systems With Gelatin Artificial Fingerprint
TLDR
The method of creating a gelatin artificial fingerprints to bypass the locking system of smartphones, laptop and tablet confirmed the possibility of bypassing fingerprint protection without the need for expensive tools or high-quality fingerprint samples. Expand
BiometricJammer: Method to Prevent Acquisition of Biometric Information by Surreptitious Photography on Fingerprints
TLDR
It is demonstrated that an implementation of the proposed method called “BiometricJammer,” a wearable device put on a fingertip, can effectively prevent the illegal acquisition of fingerprints by surreptitious photography while still enabling contact-based fingerprint sensors to respond normally. Expand
BiometricJammer: Use of Pseudo Fingerprint to Prevent Fingerprint Extraction from Camera Images without Inconveniencing Users
  • I. Echizen, Tateo Ogane
  • Computer Science
  • 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
  • 2018
TLDR
Evaluation of the improved method preventing fingerprint acquisition from photographs while still enabling contact-based fingerprint sensors to respond normally showed that it can be implemented with a less distracting appearance and that it works as well as the conventional method. Expand
Vulnerabilities of biometric systems integrated in mobile devices: An evaluation
TLDR
This paper unifies several methodologies to evaluate the security of fingerprint biometric systems embedded in mobile devices and applies this methodology on 5 different smartphones for a security evaluation and their ability to reject false fingerprints is compared. Expand
Studying WiFi and Accelerometer Data Based Authentication Method on Mobile Phones
TLDR
The proposed score-level fusion approach to authenticate the user by using WiFi and accelerometer data collected within 3 seconds when the user opens a mobile application indicates the feasibility of deploying such authentication mechanism on the mobile application. Expand
Enabling Fingerprint Presentation Attacks: Fake Fingerprint Fabrication Techniques and Recognition Performance
TLDR
Five different commercial-off-the-shelf fingerprint scanners based on different sensing technologies, including optical, optical multispectral, passive capacitive, active capacitive and thermal, are evaluated regarding their susceptibility to presentation attacks using fake fingerprint representations. Expand
Brain Password: A Secure and Truly Cancelable Brain Biometrics for Smart Headwear
TLDR
This work explores a truly cancelable brain-based biometric system for mobile platforms (e.g., smart headwear) and presents a new psychophysiological protocol via non-volitional brain response for trustworthy mobile authentication, with an application example of smart head wear. Expand
...
1
2
3
4
5
...

References

SHOWING 1-5 OF 5 REFERENCES
Learning Fingerprint Reconstruction: From Minutiae to Image
  • Kai Cao, Anil K. Jain
  • Computer Science
  • IEEE Transactions on Information Forensics and Security
  • 2015
TLDR
The proposed reconstruction algorithm outperforms the state-of-the-art reconstruction algorithms in terms of both spurious minutiae and matching performance with respect to type-I attack and type-II attack. Expand
A Survey on Antispoofing Schemes for Fingerprint Recognition Systems
TLDR
The use of artificial intelligence in the development of fingerprint recognition systems poses a serious threat to the integrity of these systems and their ability to be fooled into thinking they are real. Expand
Fingerprint image synthesis based on statistical feature models
TLDR
This paper proposes a method to synthesize fingerprint images that retain prespecified features (i.e., singular points, orientation field, and minutiae) which is validated by comparing the synthesized images with those generated by SFinGe and by investigating the match score distributions on synthesized and real fingerprint databases. Expand
Handbook of Fingerprint Recognition
TLDR
This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators. Expand
http://www.marketresearch.com/Research-Capsule-v4026/Fingerprint-Sensors-Smart-Mobile-Devices-8918844
  • http://www.marketresearch.com/Research-Capsule-v4026/Fingerprint-Sensors-Smart-Mobile-Devices-8918844