• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.69-78
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• 2023

With the global rise of digital data, the uncontrolled quantity of data is susceptible to cyber warfare or cyber attacks. Therefore, it is necessary to improve cyber security systems. This research studies the behavior of malicious acts and uses Higuchi Fractal Dimension (HFD), which is a non-linear mathematical method to examine the intricacy of the behavior of these malicious acts and anomalies within the cyber physical system. The HFD algorithm was tested successfully using synthetic time series network data and validated on real-time network data, producing accurate results. It was found that the highest fractal dimension value was computed from the DoS attack time series data. Furthermore, the difference in the HFD values between the DoS attack data and the normal traffic data was the highest. The malicious network data and the non-malicious network data were successfully classified using the Receiver Operating Characteristics (ROC) method in conjunction with a scaling stationary index that helps to boost the ROC technique in classifying normal and malicious traffic. Hence, the suggested methodology may be utilized to rapidly detect the existence of abnormalities in traffic with the aim of further using other methods of cyber-attack detection.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.873-874
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• 2008

• Korean Journal of Biological Psychiatry
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• v.16 no.2
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• pp.69-75
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• 2009

Objectives : The detrended fluctuation analysis is one of the nonlinear methods for the investigation of biological time series. It quantifies the fractal scaling properties and is known to be useful in the evaluation of long-range correlations in time series. The heart rate variability(HRV) of obstructive sleep apnea syndrome (OSAS) patients during nighttime was analyzed by detrended fluctuation analysis to assess its relationship with the severity of the symptoms. Methods : Fifty nine untreated male OSAS patients with moderate to severe symptoms(mean age=45.4${\pm}$11.7 years, apnea-hypopnea index, AHI${\geq}$15) underwent nocturnal polysomnography. Moderate(AHI=15-30, N=22) and severe(AHI>30, N=37) OSAS patients were compared for the indices derived from detrended fluctuation analysis and frequency domain analysis of HRV. Results : In the detrended fluctuation analysis, the alpha values were 0.75${\pm}$0.11 and 0.82${\pm}$0.07 for the severe and the moderate OSAS groups respectively. The difference was significant(p<.01). The alpha value had negative correlation with AHI(r=-.425, p=.001). Negative correlation coefficients were also found in the relationships between the alpha values and very low frequency(VLF)(r=-.425, p=.001), low frequency(LF)(r=-.633, p= <.001) and the LF/HF ratio(r=-.305, p=.019) respectively. LF/HF ratio(p=.005) was higher in the severe OSAS group compared to that of the moderate OSAS group. Conclusion : In this study, the detrended fluctuation analysis showed the significant difference between the two OSAS groups classified according to their severity of symptoms. The scaling exponent showed the negative correlation with AHI and indicies of frequency domain analysis. This result suggests that detrended fluctuation analysis can be helpful to estimate the severity of OSAS.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.36.2-37
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• 2016

We study the long-term radio variability of 43 radio bright AGNs by exploiting the data base of the University of Michigan Radio Astronomy Observatory (UMRAO) monitoring program. The UMRAO database provides high quality lightcurves spanning 25 - 32 years in time at three observing frequencies, 4.8, 8, and 14.5 GHz. We model the periodograms (temporal power spectra) of the observed lightcurves as simple power-law noise (red noise, spectral power $P(f){\propto}f^{-{\beta}}$ using Monte Carlo simulations, taking into account windowing effects (red-noise leak, aliasing). The power spectra of 39 (out of 43) sources are in good agreement with the models, yielding a range in power spectral index (${\beta}$) from ${\approx}1$ to ${\approx}3$. We find a strong anti-correlation between ${\beta}$ and the fractal dimension of the lightcurves, which provides an independent check of the quality of our modelling of power spectra. We fit a Gaussian function to each flare in a given lightcurve to obtain the flare duration. We discover a correlation between ${\beta}$ and the median duration of the flares. We use the derivative of a lightcurve to obtain a characteristic variability timescale which does not depend on the assumed functional form of the flares, incomplete fitting, and so on. We find that, once the effects of relativistic Doppler boosting on the observed timescales are corrected, the variability timescales of our sources are proportional to the black hole mass to the power of ${\alpha}=1.70{\pm}0.49$. We see an indication for AGNs in different regimes of accretion rate, flat spectrum radio quasars and BL Lac objects, having different scaling relations with ${\alpha}{\approx}1$ and ${\approx}2$, respectively. We find that modelling the periodograms of four of our sources requires the assumption of broken powerlaw spectra. From simulating lightcurves as superpositions of exponential flares we conclude that strong overlap of flares leads to featureless simple power-law periodograms of AGNs at radio wavelengths in most cases (The paper is about to be submitted to ApJ).