Cognitive Cybersecurity

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Authors: Anirudh Maurya, Ankan K. Mondal, Kahkashan Siddavatam
Cited by: 0

Abstract

Sophisticated threats that occur in today’s fast-moving environment that remain difficult to combat by regular people are cyberattacks, examples of such threats include advanced malware attacks, data breaches, phishing scams, ransomware incidents, and network vulnerabilities. This chapter presents symbolic deep learning (SDL) as a new approach for emulating the decision-making processes of cybersecurity experts. By using a small fraction of expert decision data, SDL enables the creation of simple, interpretable models that bring advanced decision-making capabilities to a broader audience. Due to this ever-evolving threat landscape, we need to use advancing methodologies like SDL to combat cyber security challenges. Not only is SDL smart, it is uncomplicated and clear too. It explains the decisions made by cybersecurity experts. From a limited data sample, it reconstructs expert decision-making processes that are usually informed by implicit, experience-based knowledge. That is to say, even if a person is not skilled in the use of technology, be that as it may, said person can still get hold of professional help in making technological decisions. Ultimately, cyber defenses against online attacks become stronger by using the model developed by SDL. What is interesting about the SDL methodology, in and of itself, is the way it combines the lead cutting edge deep learning (DL) technologies with peer review, and other more traditional, time-tested approaches. It’s like decoding the secret patterns in how experts make choices. SDL is superior by comparison to standard tech because it pulls from the wisdom and knowledge of numerous experts from varying sources. The strength of this approach lies not in the volume of expert knowledge it utilizes, but in the quality of that knowledge. Reliable, high-quality information is ultimately more valuable than large quantities of data. This keeps tech users strong against the ever-changing threats on the internet. In other words, SDL is the friendly superhero in this tale of cyber defense; wrestling with tricky problems, breaking down expert choices into small digestible bites, and allowing everyone to make smarter decisions. Generally speaking, it is almost like having a team of experts in cybersecurity right at your fingertips to protect the world from online attacks.

Fields of Study & Subjects

Information and Cyber Security Network Security and Intrusion Detection Adversarial Robustness in Machine Learning

Publication details

Journal / source
CRC Press eBooks
Pages
44–62
Publication date
27 February 2026
Language
EN
Document type
Book chapter