Data Science for Cyber Security- Opportunities vs. Challenges

*Disclaimer: This blog is focused on a very high level understanding of some opportunities and challenges of using data science in cyber security industry. If you are looking for more in-depth technical approach, this might not be the right blog. I value your time for what you will gain on what you spend. In future, I will definitely like to write some technical blogs in this subject area.

If you are still reading, that’s great. Lets cruise…The field of cybersecurity — both offensive and defensive security has come along a long way since the first computer virus called Creeper, created by Bob Thomas in 1971, that successfully disguised itself to move from one host to another within the intranet and leaving its trail on the hosts. The program was a research project, and it was not intended to harm anything.

In today’s era, where we have a massive spider web of internet, the attack surface is huge, and we are not talking about simple programs but advanced persistent threats. They are advanced because the attackers/hackers have a full spectrum of intelligence-gathering techniques at their disposal. They are persistent because they like to follow a ‘low-and-slow’ approach to intrude and maintain long-term access on the target devices. They are threats because they have both capability and intent to harm.