26 citations · 33 across the 6 of their papers we have counts for
5 papers · 1 filter
New data poison attacks on machine learning classifiers for mobile exfiltration
Miguel A. Ramirez, Sangyoung Yoon, Ernesto Damiani +7
Most recent studies have shown several vulnerabilities to attacks with the potential to jeopardize the integrity of the model, opening in a few recent years a new window of opportu…
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey
Miguel A. Ramirez, Song-Kyoo Kim, Hussam Al Hamadi +5
Machine learning models have been widely adopted in several fields. However, most recent studies have shown several vulnerabilities from attacks with a potential to jeopardize the…
An Enhanced Machine Learning-based Biometric Authentication System Using RR-Interval Framed Electrocardiograms
Amang Song-Kyoo Kim, Chan Yeob Yeun, Paul D. Yoo
This paper is targeted in the area of biometric data enabled security system based on the machine learning for the digital health. The disadvantages of traditional authentication s…
An Enhanced Electrocardiogram Biometric Authentication System Using Machine Learning
Ebrahim Al Alkeem, Song-Kyoo Kim, Chan Yeob Yeun +3
Traditional authentication systems use alphanumeric or graphical passwords, or token-based techniques that require "something you know and something you have". The disadvantages of…
A Machine Learning Framework for Biometric Authentication using Electrocardiogram
Song-Kyoo Kim, Chan Yeob Yeun, Ernesto Damiani +1
This paper introduces a framework for how to appropriately adopt and adjust Machine Learning (ML) techniques used to construct Electrocardiogram (ECG) based biometric authenticatio…