Bring Your Own Device (BYOD) Security Threats and Mitigation Mechanisms: Systematic Mapping
Author:
Affiliation:
1. University of Lafia,Faculty of Computing Federal,Department of Computer Science,Nasarawa State,Nigeria
2. University of Malaya,Faculty of Computer Science & IT,Department of Information Systems,Kuala Lumpur,Malaysia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9791459/9791467/09791907.pdf?arnumber=9791907
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5. Fingerprint Spoofing Detection to Improve Customer Security in Mobile Financial Applications Using Deep Learning;arora;Arabian Journal for Science and Engineering,2019
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1. Data-Driven Design for Anomaly Detection in Network Access Control Systems;2023 International Conference on Business Analytics for Technology and Security (ICBATS);2023-03-07
2. Machine learning approach for detecting and combating bring your own device (BYOD) security threats and attacks: a systematic mapping review;Artificial Intelligence Review;2023-01-17
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