Leveraging Computational Intelligence Techniques for Defensive Deception: A Review, Recent Advances, Open Problems
Pilla Vaishno Mohan1, Shriniket Dixit1, Amogh Gyaneshwar1
1School of Computer Science and Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.
Sensors (Basel, Switzerland)
|March 26, 2022
Summary
Defensive deception uses artificial intelligence to counter cyberattacks by creating uncertainty for adversaries. This survey explores deep learning and machine learning for advanced deception frameworks to enhance cybersecurity defenses.
Area of Science:
- Cybersecurity
- Artificial Intelligence
- Information Warfare
Background:
- Information systems face daily global attacks, necessitating advanced defense strategies.
- Defensive deception, inspired by warfare, aims to counter cyber threats by introducing uncertainty.
- Existing deception tactics include honeypots, honeytokens, and moving target defense.
Purpose of the Study:
- To provide a comprehensive survey of defensive deception tactics utilizing artificial intelligence.
- To highlight the need for a quantitative framework for deploying advanced deception technologies.
- To analyze the application of deep learning and machine learning in defensive deception.
Main Methods:
- Review and analysis of existing literature on defensive deception.
- Focus on the integration of computational intelligence, specifically deep learning and machine learning.
- Identification of insights, lessons, and limitations from prior research.
Main Results:
- Computational intelligence offers tools for advanced deception frameworks.
- Deep learning and machine learning are key strategies for implementing defensive deception.
- Prior work provides valuable insights but also reveals limitations in current approaches.
Conclusions:
- There is a critical need for a comprehensive framework for advanced deception technologies.
- Future research should address identified gaps in defensive deception strategies.
- AI-powered defensive deception holds significant potential for enhancing cybersecurity.
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