GENERATIVE NEURAL NETWORK APPROACHES FOR ADAPTIVE BUILDING ENERGY FORECASTING AND CONTROL: A REVIEW OF METHODS AND MICROSERVICES ARCHITECTURES

Abstract

Phishing attacks remain one of the most widespread cyber threat vectors, as they combine technical mechanisms
for compromising information systems with social engineering techniques. At the same time, existing phishing detection
approaches are primarily focused on analyzing the technical parameters of an attack and do not provide a formalized
transition from detection results to identifying the characteristics of the attacker, which complicates cyberattack
attribution, cyber threat intelligence, and information security incident response. The aim of this study is to develop a
method for constructing a social engineer profile based on the analysis of a detected phishing attack on an information
system. The proposed method is based on extending a generalized tuple by integrating a set of attacker profile features
formed according to the set-theoretic classification model of modern social engineering attack implementation approaches
and the parameters of the detected phishing attack. The method consists of four main stages: constructing a formalized
representation of the phishing attack, determining the characteristics of the social engineer profile, constructing an
integrated social engineer profile, and visualizing the resulting profile. Unlike existing approaches, the proposed method
provides a formalized transition from the parameters of a detected phishing attack to the construction of an integrated
profile of its perpetrator. The proposed method was validated using a representative phishing attack, resulting in the
construction of a social engineer profile, identification of its key characteristics, and generation of a diagram that provides
a graphical representation of the resulting profile. The obtained results can be used to support cyberattack attribution,
cyber threat intelligence, information security incident response, and the development of countermeasures against social
engineering attacks.
Keywords: phishing, social engineer profile, attacker profile, social engineering, cyber threat intelligence,
information security.

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