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A Study on the Psychology of Social Engineering-Based Cyberattacks and Existing Countermeasures
Open accessAbstract
As cybersecurity strategies become more robust and challenging, cybercriminals are mutating cyberattacks to be more evasive. Recent studies have highlighted the use of social engineering by criminals to exploit the human factor in an organization’s security architecture. Social engineering attacks exploit specific human attributes and psychology to bypass technical security measures for malicious acts. Social engineering is becoming a pervasive approach used for compromising individuals and organizations (is relatively more convenient to compromise a human compared to discovering a vulnerability in the security system). Social engineering-based cyberattacks are extremely difficult to counter as they do not follow specific patterns or approaches for conducting an attack, making them highly effective, efficient, easy, and obscure approaches for compromising any organization. To counter such attacks, a better understanding of the attack tactics is highly essential. Hence, this paper provides an in-depth analysis of the approaches used to conduct social engineering-based cyberattacks. This study discusses human vulnerabilities employed by criminals in recent security breaches. Further, the paper highlights the existing approaches, including machine learning-based methods, to counter social engineering-based cyberattacks.
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“As a result, sending packets with incorrect checksums makes it easier for attackers to collect data from systems with poor configuration by looking for a response [266] [216].”
From Comparative Analysis of Intrusion Detection Systems and Machine Learning Based Model Analysis through Decision Tree (2023) · cites this paper as [216]
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Metadata
- Authors
- Siddiqi, M. A., Pak, W., & Siddiqi, M. A.
- Affiliations
- University of Karachi (PK)
- Yeungnam University (KR)
- Corresponding author
- Pak, Wooguil
- Venue
- Applied Sciences
- Publisher
- MDPI AG
- Published
- 2022-06-14
- Volume
- 12
- Issue
- 12
- Pages
- 6042
- ISSN
- 2076-3417 (ISSN-L)
- OpenAlex
- W4282920965
- Cited by
- 118
- References
- 69
- Citations by year
- 2026: 24 · 2025: 35 · 2024: 29 · 2023: 26 · 2022: 4
- FWCI
- 23.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Applied Sciences (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Research Foundation of Korea (NRF) (NRF-2022R1A2C1011774)
- 2022 Yeungnam University (NRF-2022R1A2C1011774)
- Topics
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Keywords
- social engineering, cyberattacks, human factors in security, human vulnerability, offensive strategy, countermeasures, machine learning detection, security breaches, psychological manipulation
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