An Overview of Phishing Victimization: Human Factors, Training and the Role of Emotions

• URL: http://arxiv.org/abs/2209.11197v1
• Date: Tue, 13 Sep 2022 12:51:20 GMT
• Title: An Overview of Phishing Victimization: Human Factors, Training and the Role of Emotions
• Authors: Mousa Jari
• Abstract summary: Phishing is a form of cybercrime that allows criminals, phishers, to deceive end users in order to steal their confidential and sensitive information. This paper explores the emotional factors that have been reported in previous studies to be significant in phishing victimization.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Phishing is a form of cybercrime and a threat that allows criminals, phishers, to deceive end users in order to steal their confidential and sensitive information. Attackers usually attempt to manipulate the psychology and emotions of victims. The increasing threat of phishing has made its study worthwhile and much research has been conducted into the issue. This paper explores the emotional factors that have been reported in previous studies to be significant in phishing victimization. In addition, we compare what security organizations and researchers have highlighted in terms of phishing types and categories as well as training in tackling the problem, in a literature review which takes into account all major credible and published sources.

Related papers

• Rethinking the Vulnerabilities of Face Recognition Systems:From a Practical Perspective [53.24281798458074]
  Face Recognition Systems (FRS) have increasingly integrated into critical applications, including surveillance and user authentication. Recent studies have revealed vulnerabilities in FRS to adversarial (e.g., adversarial patch attacks) and backdoor attacks (e.g., training data poisoning)
  arXiv  Detail & Related papers  (2024-05-21T13:34:23Z)
• Evaluating the Efficacy of Large Language Models in Identifying Phishing Attempts [2.6012482282204004]
  Phishing, a prevalent cybercrime tactic for decades, remains a significant threat in today's digital world. This paper aims to analyze the effectiveness of 15 Large Language Models (LLMs) in detecting phishing attempts.
  arXiv  Detail & Related papers  (2024-04-23T19:55:18Z)
• The Anatomy of Deception: Technical and Human Perspectives on a Large-scale Phishing Campaign [4.369550829556578]
  This study takes an unprecedented deep dive into large-scale phishing campaigns aimed at Meta's users. Analysing data from over 25,000 victims worldwide, we highlight the nuances of these campaigns. Through the application of advanced computational techniques, including natural language processing and machine learning, this work unveils critical insights into the psyche of victims.
  arXiv  Detail & Related papers  (2023-10-05T12:24:24Z)
• Graph Mining for Cybersecurity: A Survey [61.505995908021525]
  The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Traditional Machine Learning (ML) based methods are extensively used in detecting cyber threats, but they hardly model the correlations between real-world cyber entities. With the proliferation of graph mining techniques, many researchers investigated these techniques for capturing correlations between cyber entities and achieving high performance.
  arXiv  Detail & Related papers  (2023-04-02T08:43:03Z)
• Tainted Love: A Systematic Review of Online Romance Fraud [68.8204255655161]
  Romance fraud involves cybercriminals engineering a romantic relationship on online dating platforms. We characterise the literary landscape on romance fraud, advancing the understanding of researchers and practitioners. Three main contributions were identified: profiles of romance scams, countermeasures for mitigating romance scams, and factors that predispose an individual to become a scammer or a victim.
  arXiv  Detail & Related papers  (2023-02-28T20:34:07Z)
• Fighting Malicious Media Data: A Survey on Tampering Detection and Deepfake Detection [115.83992775004043]
  Recent advances in deep learning, particularly deep generative models, open the doors for producing perceptually convincing images and videos at a low cost. This paper provides a comprehensive review of the current media tampering detection approaches, and discusses the challenges and trends in this field for future research.
  arXiv  Detail & Related papers  (2022-12-12T02:54:08Z)
• SoK: Human-Centered Phishing Susceptibility [4.794822439017277]
  We propose a three-stage Phishing Susceptibility Model (PSM) for explaining how humans are involved in phishing detection and prevention. This model reveals several research gaps that need to be addressed to improve users' detection performance.
  arXiv  Detail & Related papers  (2022-02-16T07:26:53Z)
• Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text [219.15486286590016]
  This paper introduces a dynamic deep ensemble model for spam detection that adjusts its complexity and extracts features automatically. As a result, the model achieved high precision, recall, f1-score and accuracy of 98.38%.
  arXiv  Detail & Related papers  (2021-10-10T17:19:37Z)
• Falling for Phishing: An Empirical Investigation into People's Email Response Behaviors [10.841507821036458]
  Despite sophisticated phishing email detection systems, humans continue to be tricked by phishing emails. We have carried out an empirical study to investigate people's thought processes when reading their emails. We identify eleven factors that influence people's response decisions to both phishing and legitimate emails.
  arXiv  Detail & Related papers  (2021-08-10T16:19:01Z)
• Detecting Phishing Sites -- An Overview [0.0]
  Phishing is one of the most severe cyber-attacks where researchers are interested to find a solution. To minimize the damage caused by phishing must be detected as early as possible. There are various phishing detection techniques based on white-list, black-list, content-based, URL-based, visual-similarity and machine-learning.
  arXiv  Detail & Related papers  (2021-03-23T19:16:03Z)
• Phishing and Spear Phishing: examples in Cyber Espionage and techniques to protect against them [91.3755431537592]
  Phishing attacks have become the most used technique in the online scams, initiating more than 91% of cyberattacks, from 2012 onwards. This study reviews how Phishing and Spear Phishing attacks are carried out by the phishers, through 5 steps which magnify the outcome.
  arXiv  Detail & Related papers  (2020-05-31T18:10:09Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.