[vc_row full_width=”stretch_row_content” css=”.vc_custom_1763466045344{background-color: #6B15C4 !important;}”][vc_column][vc_custom_heading text=”Research” font_container=”tag:h1|font_size:48|text_align:center|color:%23FFFBFB” google_fonts=”font_family:Raleway%3A100%2C200%2C300%2Cregular%2C500%2C600%2C700%2C800%2C900|font_style:700%20bold%20regular%3A700%3Anormal” css=””][vc_custom_heading text=”CyberSecurity x Artificial Intelligence” font_container=”tag:h3|font_size:24|text_align:center|color:%23FFFBFB” google_fonts=”font_family:Raleway%3A100%2C200%2C300%2Cregular%2C500%2C600%2C700%2C800%2C900|font_style:400%20regular%3A400%3Anormal” css=”.vc_custom_1763462463330{margin-top: -20px !important;}”][/vc_column][/vc_row][vc_row][vc_column width=”3/4″][vc_column_text css=””]

I’m Dr. Kaushal Bhavsar. Research has shaped my entire journey in cybersecurity—especially where security, AI, and human behaviour cross paths.

I like solving problems that matter. My work always aims for one thing:
real-world impact, not theoretical complexity.

Research Focus

Over the past decade, I’ve explored topics across:

  • Malware analysis

  • Web application security

  • Behavioral analytics

  • Insider-threat prediction with deep learning

  • Phishing detection and digital forensics

My approach is straightforward: understand how attackers think, model human behaviour, and build systems that detect threats before they reach production.

 

Featured Work

Malware Analysis Techniques

Early in my career, I focused on reverse-engineering malware and understanding attacker behavior. This foundation still guides my thinking today.

Web Application Vulnerability Prevention

I worked on strategies to help organizations identify and block weaknesses in their web stack before attackers exploit them.

Insider Threat Detection using Deep Learning

This was the core of my PhD. I analyzed behavioral signals and applied neural networks to predict insider threats in real time. I published multiple works in this area.

Phishing Detection & Digital Forensics

More recently, I’ve explored machine learning approaches for phishing detection and internal forensics.

👉 Full list of publications is available on my Google Scholar profile.

What I’m Working On Now

These days, I’m interested in:

  • AI-driven detection systems

  • Automated security tooling

  • Using LLMs to enhance malware analysis and incident response

  • Behavioural signals in modern cloud and SaaS environments

I also enjoy mentoring researchers and helping them build clarity, structure, and momentum in their work.

If you would like to collaborate or discuss research ideas, please don’t hesitate to reach out.

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110+

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Citations

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10+

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Years of Research

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10+

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Research papers

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Impact

  • 110+ citations

  • h-index: 5

  • i10-index: 3

My work has influenced both academic research and practical security engineering. I focus on building ideas that move beyond theory and help real teams secure real systems.

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Patent

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US Patent 12361127 B1 — “Computer-based Systems Configured For Malware Detection And Methods Of Use Thereof”

This patent covers my work on detecting malicious changes in websites using browser-driven visual behavioural analysis and automated diffing.

 

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