journal article·2022-06-14Open access

A Study on the Psychology of Social Engineering-Based Cyberattacks and Existing Countermeasures

Murtaza Ahmed Siddiqi, Wooguil Pak, Moquddam A. Siddiqi

Applied Sciences· Volume 12· Issue 12

Abstract

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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Information and Cyber Security · Cybercrime and Law Enforcement Studies · Network Security and Intrusion Detection

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea

Department of Sociology, University of Karachi, Karachi 75270, Pakistan

Funding

National Research Foundation of Korea (NRF) · 2022 Yeungnam University

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