I’m happy to share that Part Three of my blog series on image analysis in cybersecurity is now live on Hornetsecurity’s website!
In this latest article, I explore advanced techniques for detecting near-duplicate images, which go beyond hash-based methods and color histograms. As attackers grow more sophisticated, modifying visual content just enough to evade detection, our defenses must evolve too.
This post dives into content-based approaches, including object recognition, embedded text comparison, and hybrid techniques, to help security systems spot even the most cleverly disguised threats.
If you missed it, Part Two covered foundational techniques like hash matching and histogram analysis. You can read it here.
Check out the full article: Detection of Cyberthreats with Computer Vision (Part 3).
As always, I’d love to hear your feedback, and stay tuned for more on computer vision in cybersecurity!
