Recently, when I was reading up on Cyber Security & Threat Detection, I came across “The Annual Data Breach Report by Verizon”. The report analyzed thousands of such incidents reported by various companies, public & private organizations which happened over the last couple of years. The report analyzed breaches by firmographics, geographies, industries etc. and found that cyber intrusion is a growing threat to every industry based in every country of the world. The report proves time and again that “No single industry or organization in the world is safe from Cyber Threats”. This piqued my curiosity & we felt that we could use all the goodness of data science to effectively tackle this problem. I designed a Threat/Intrusion Detection System, which could be used to detect such data leaks/breaches & take a preventive action to contain, if not stop the damage due to breach.
What is Deep Learning?
Traditional Machine Learning had used handwritten features and modality-specific machine learning to classify images, text or recognize voices. Deep learning / Neural network identifies features and finds different patterns automatically. Time to build these complex tasks has been drastically reduced and accuracy has exponentially increased because of advancements in Deep learning. Neural networks have been partly inspired from how 86 billion neurons work in a human and become more of a mathematical and a computer problem. We will see by the end of the blog how neural networks can be intuitively understood and implemented as a set of matrix multiplications, cost function, and optimization algorithms.
Biological analogy of Neural Network