Title Computer vision and deep learning provide new ways to detect cyber threats Degree of recognition International Media name/outlet TechTalks Media type Web Country/Territory United Kingdom Date 10/09/21 Description The last decade’s growing interest in deep learning was triggered by the proven capacity of neural networks in computer vision tasks. If you train a neural network with enough labeled photos of cats and dogs, it will be able to find recurring patterns in each category and classify unseen images with decent accuracy. URL https://bdtechtalks.com/2021/09/10/computer-vision-deep-learning-threat-detection/ Persons Stavros Shiaeles Title Machine learning technique detects phishing sites based on markup visualization Degree of recognition International Media name/outlet portswigger.net Media type Web Country/Territory United Kingdom Date 8/09/21 Description Machine learning models trained on the visual representation of website code can help improve the accuracy and speed of detecting phishing websites.
This is according to a paper (PDF) by security researchers at the University of Plymouth and the University of Portsmouth, UK.
Producer/Author Ben Dickson URL https://portswigger.net/daily-swig/machine-learning-technique-detects-phishing-sites-based-on-markup-visualization Persons Stavros Shiaeles
Title SN Applied Sciences Webinar Degree of recognition International Media name/outlet YouTube Media type Web Country/Territory United Kingdom Date 27/10/21 Description Stavros Shiaeles discusses Machine Learning Anomaly Detection using Binary Visualisation Producer/Author Springer Nature Group URL https://www.youtube.com/watch?v=8QNK1AHLmxM Persons Stavros Shiaeles