Time-Based Model of the Success of a Malefactor’s Multistep Social Engineering Attack on a User

Khlobystova, Anastasiia O.; Abramov, Maxim V.

doi:10.1007/978-3-030-87178-9_22

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Another research proposed detailed models of social engineering attacks, mapping real-world examples to an attack framework [9]. Additionally, a study introduced a multi-stage analysis approach to social engineering attacks, considering the attacker's accidental factors [10].…”

Section: Related Workmentioning

confidence: 99%

APSEA: An Awareness and Prevention Expert System against Social Engineering Attacks in Public Organizations

Cardoso,

Ribeiro,

Silva

2024

Preprint

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The growing concern for information security arises from the risks associated with the dissemination of personal data on the internet and the increasing incidents of social engineering attacks, which exploit psychological vulnerabilities. These attacks pose a substantial threat to individuals and organizations, potentially resulting in significant financial losses. This article highlights the development of the APSEA tool - Awareness and Prevention Expert System against Engineering Attacks, an expert system designed to raise awareness and prevent social engineering attacks in public organizations. The tool aims to make employees vigilant against such threats, empowering them to identify and avoid psychological manipulation techniques used by attackers. Despite existing protective measures such as awareness training and security policies, APSEA seeks to contribute to strengthening the human factor in information security. The article covers key concepts in information security, presenting interactive modules and artificial intelligence features to identify vulnerabilities. A qualitative and performance evaluation of the tool is conducted, and the results indicate that the adopted approach is effective in achieving its objectives.

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Section: Related Workmentioning

confidence: 99%

APSEA: An Awareness and Prevention Expert System against Social Engineering Attacks in Public Organizations

Cardoso,

Ribeiro,

Silva

2024

Preprint

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“…For example, there exist automated systems for determining depression [12,16]. Moreover, these associations can be viewed as a part of the user profiling process that plays an important role in assessing an estimation of the users' protection from social engineering attacks [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Associations between the Avatar Characteristics and Psychometric Test Results of VK Social Media Users

Stoliarova,

Bushmelev,

Abramov

2023

Mathematics

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Online social media has an increasing influence on people’s lives, providing tools for communication and self–representation. People’s digital traces are gaining attention as a reflection of their personality traits, enhancing the personality computing tasks in various areas. This study aims at the identification of statistical associations between psychometric scores from three questionnaires—the Big Five Inventory, Plutchik’s Lifestyle Index and the Eysenck Personality Questionnaire—and a set of graphical features of avatar images from the VK online social media that include the pixel characteristics from the HSV and RGB color models and the number of persons and faces depicted in an avatar. The problem is considered from the statistical point of view. The dependency between psychometric scores and the number of faces/persons is assessed with the Kruskal–Wallis test with Dunn test pairwise comparisons. The color-pixel characteristics that are associated with the psychometric scores are selected with several fits of the regularized regression with L2 and MCP penalties. The data for the study were collected via a specially developed application for the online social media platform VK. The results of the analysis support existing research on how colors express personality and discover certain color-pixel image characteristics that could be used for personality computing models.

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Deep Machine Learning Techniques in the Problem of Estimating the Expression of Psychological Characteristics of a Social Media User

Bushmelev

Khlobystova

Abramov

et al. 2023

Studies in Systems, Decision and Control

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Time-Based Model of the Success of a Malefactor’s Multistep Social Engineering Attack on a User

Cited by 3 publications

References 18 publications

APSEA: An Awareness and Prevention Expert System against Social Engineering Attacks in Public Organizations

APSEA: An Awareness and Prevention Expert System against Social Engineering Attacks in Public Organizations

Associations between the Avatar Characteristics and Psychometric Test Results of VK Social Media Users

Deep Machine Learning Techniques in the Problem of Estimating the Expression of Psychological Characteristics of a Social Media User

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