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Application of Game Theoretic Model for Cyber Threat Intelligence Framework
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In the ever-evolving landscape of cybersecurity, the application of game
theoretic models has emerged as a powerful and innovative approach to
enhance our understanding and management of cyber threats. This abstract
explores the application of a variant of game theoretic models within
the context of a Cyber Threat Intelligence (CTI) framework. With the
proliferation of cyber-attacks targeting critical infrastructure,
sensitive data, and national security, it has become imperative to
develop proactive and adaptive strategies for threat detection,
mitigation, and response. The variant of game theoretic models discussed
in this abstract departs from traditional game theory by incorporating
elements of dynamic adaptation and machine learning. This adaptation
enables the framework to model and analyze the intricate and rapidly
changing interactions between threat actors and defenders in real-time,
thereby providing a more accurate representation of the evolving threat
landscape. By leveraging machine learning algorithms, the model can
continuously learn and adapt to new threats and tactics, making it a
versatile tool for CTI. This abstract also explores the practical
applications of the variant model in various aspects of cybersecurity,
including threat actor profiling, vulnerability assessment, and decision
support for incident response. By considering the strategic motivations
and behaviors of threat actors, organizations can make informed
decisions regarding resource allocation, risk assessment, and security
investments. The integration of this variant of game theoretic models
into CTI holds great potential to revolutionize our approach to
cybersecurity, enabling organizations to stay one step ahead of
adversaries. As the digital world becomes increasingly complex, the
ability to predict, mitigate, and adapt to cyber threats is crucial for
safeguarding critical assets and ensuring the resilience of digital
infrastructure. This paper highlights the significance of this
innovative approach and its potential to shape the future of cyber
threat intelligence and cybersecurity practices.
Title: Application of Game Theoretic Model for Cyber Threat Intelligence Framework
Description:
In the ever-evolving landscape of cybersecurity, the application of game
theoretic models has emerged as a powerful and innovative approach to
enhance our understanding and management of cyber threats.
This abstract
explores the application of a variant of game theoretic models within
the context of a Cyber Threat Intelligence (CTI) framework.
With the
proliferation of cyber-attacks targeting critical infrastructure,
sensitive data, and national security, it has become imperative to
develop proactive and adaptive strategies for threat detection,
mitigation, and response.
The variant of game theoretic models discussed
in this abstract departs from traditional game theory by incorporating
elements of dynamic adaptation and machine learning.
This adaptation
enables the framework to model and analyze the intricate and rapidly
changing interactions between threat actors and defenders in real-time,
thereby providing a more accurate representation of the evolving threat
landscape.
By leveraging machine learning algorithms, the model can
continuously learn and adapt to new threats and tactics, making it a
versatile tool for CTI.
This abstract also explores the practical
applications of the variant model in various aspects of cybersecurity,
including threat actor profiling, vulnerability assessment, and decision
support for incident response.
By considering the strategic motivations
and behaviors of threat actors, organizations can make informed
decisions regarding resource allocation, risk assessment, and security
investments.
The integration of this variant of game theoretic models
into CTI holds great potential to revolutionize our approach to
cybersecurity, enabling organizations to stay one step ahead of
adversaries.
As the digital world becomes increasingly complex, the
ability to predict, mitigate, and adapt to cyber threats is crucial for
safeguarding critical assets and ensuring the resilience of digital
infrastructure.
This paper highlights the significance of this
innovative approach and its potential to shape the future of cyber
threat intelligence and cybersecurity practices.
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