Title: Methodology of wavelet analysis in research of dynamics of phishing attacks

Authors: Mehdi Dadkhah; Vyacheslav V. Lyashenko; Zhanna V. Deineko; Shahaboddin Shamshirband; Mohammad Davarpanah Jazi

Addresses: Department of Computer and Information Technology, Foulad Institute of Technology, Foulad Shahr, Isfahan 8491663763, Iran ' Department of Informatics, Faculty of Applied Mathematics and Management, Kharkov National University of Radio Electronics, 14 Lenina Str., Kharkov 61166, Ukraine ' Department of Media Systems and Technology, Kharkov National University of Radio Electronics, 14 Lenina Str., Kharkov 61166, Ukraine ' Department of Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam; Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam ' Department of Computer and Information Technology, Foulad Institute of Technology, Foulad Shahr, Isfahan 8491663763, Iran

Abstract: Safety of transfer and reception of various data over the internet can be accompanied by a presence of harmful components in a passed content. The phishing attack is one of versions of such harmful components. Thus it is important to know the relationship between the phishes verified as valid and suspected phishes Submitted. This is necessary for the forecast. To solve this problem, we use the wavelet analysis of time series which represent phishes verified as valid and suspected phishes submitted. We are considering the change of Hurst indicator; we analyse of a spectrum of wavelet energy. This allows you to identify the features of the main characteristics of time series which are considered. Conducted researches have shown the presence of essential duration of long-term dependence of investigated data. We also identified presence of trend component in structure of investigated series of data. It allows you to investigate recurrence of occurrence of phishing attacks that allows concentrating forces and means during the periods of activisation of such harmful influences. The analysis is spent on real data that reflects the importance of the conclusions obtained.

Keywords: internet; phishing; trend; wavelet analysis; wavelet energy; wavelet expansion; Hurst indicator; Daubechies wavelet.

DOI: 10.1504/IJAIP.2019.098561

International Journal of Advanced Intelligence Paradigms, 2019 Vol.12 No.3/4, pp.220 - 238

Received: 08 Jan 2016
Accepted: 04 Apr 2016
Published online: 28 Mar 2019 *

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