Using of fuzzy cognitive modeling in information security systems constructing

Кulyk, Mykola; Khoma, Volodymyr; Kozlovskyi, Valerii; Mischenko, A. V.; Khlaponin, Yurii; Janisz, Karina; Fałat, Paweł

doi:10.1109/idaacs.2015.7340768

Cited by 2 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The measurement science is essential for the progress in the such conventional areas as: science and technologies [1][2][3], ecology [4], medicine [5][6][7], but recently also finds application in economy [8] forensics [9], cybersecurity [10]. A new trend in metrology is the use of robust approaches and machine learning technologies to improve metrological characteristics of measuring tools, including increased accuracy of measurements [11,12].…”

Section: Introductionmentioning

confidence: 99%

Metrology and Measurement Systems

Jun,

Szmajda,

Khoma

et al. 2020

View full text Add to dashboard Cite

The aim of this paper is to compare the efficiency of various outlier correction methods for ECG signal processing in biometric applications. The main idea is to correct anomalies in various segments of ECG waveform rather than skipping a corrupted ECG heartbeat in order to achieve better statistics. Experiments were performed using a self-collected Lviv Biometric Dataset. This database contains over 1400 records for 95 unique persons. The baseline identification accuracy without any correction is around 86%. After applying the outlier correction the results were improved up to 98% for autoencoder based algorithms and up to 97.1% for sliding Euclidean window. Adding outlier correction stage in the biometric identification process results in increased processing time (up to 20%), however, it is not critical in the most use-cases.

show abstract