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Integrating Behavioral Science and Cyber Threat Intelligence (CTI) to Counter Advanced Persistent Threats (APTs) and Reduce Human-Enabled Security Breaches

Authors: Matthew Onuh Ijiga; Hamed Salam Olarinoye; Francis Asare Baffour Yeboah; Joy Nnenna Okolo;

Integrating Behavioral Science and Cyber Threat Intelligence (CTI) to Counter Advanced Persistent Threats (APTs) and Reduce Human-Enabled Security Breaches

Abstract

As cyber threats become increasingly sophisticated, human factors remain one of the most exploited vulnerabilities in security breaches, particularly in the context of Advanced Persistent Threats (APTs). Traditional cybersecurity approaches focus on technological defenses, yet they often overlook the cognitive biases, social engineering tactics, and decision-making errors that adversaries exploit. This review explores the integration of behavioral science with CTI as a strategic approach to counter APTs and mitigate human-enabled security breaches. By examining cognitive vulnerabilities, psychological manipulation techniques, and behavior-based interventions, this study highlights the need for adaptive security frameworks that incorporate human-centric defenses. Additionally, the role of artificial intelligence and machine learning in enhancing behavior-based threat detection and response is discussed. The review further addresses challenges in integrating behavioral insights with CTI, ethical considerations, and emerging advancements in human-centric cybersecurity models. Ultimately, this paper advocates for a multidisciplinary approach that combines behavioral science and CTI to develop proactive, intelligence-driven security strategies capable of addressing the evolving cyber threat landscape.

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    7
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
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