Using Deep Learning for Information Security  

In the next few years, deep learning and machine learning will transform and expand as a decision engine across every enterprise business layer from product development to operations to finance to sales. While, internet biggies like Google, Facebook, Microsoft, and Salesforce have already embedded deep learning into their products, the information industry is also catching up to leverage it for various use cases.

Deep learning is not a silver bullet that can solve all the cybersecurity problems because it needs extensive labeled datasets and no such labeled datasets are readily available. However, there are several cybersecurity use cases where the deep learning networks are making significant improvements to the existing solutions. Malware detection and network intrusion detection are two such areas where deep learning has shown significant improvements over the rule-based and machine learning-based solutions.

In this talk, I will be providing both depth and breadth about using deep learning for the Information Security (InfoSec). I will answer the following questions:

  • Where can we apply deep learning for information security?
  • How to build a deep learning network?
  • What are the popular networks that can be leveraged in the InfoSec domain?
  • We shall walk through with multiple datasets and build various deep learning networks from scratch and discuss details of their parameters and fundamentals.
Who should attend this session?
Data Analysts, Security Analysts, Security Data Scientists, Budding Data Scientists, Information Security Professionals.
Basic knowledge of data science and deep learning is required.


Dr. Satnam Singh

Dr Satnam Singh is currently leading security data science development at Acalvio Technologies. He has more than a decade of work experience in successfully building data products from concept to production in multiple domains. In 2015, he was named as one of the top 10 data scientists in India. To his credit, he has 25+ patents and 30+ journal and conference publications.

Apart from holding a PhD degree in ECE from University of Connecticut, Satnam also holds a Masters in ECE from University of Wyoming. Satnam is a senior IEEE member and a regular speaker in various Big Data and Data Science conferences.

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