I Survived RSA 2017
RSA is over and I’m still standing (just barely). Last week was a whirlwind of activity, full of sessions, keynotes, a hectic show floor, after parties, and networking. After so much going on, I wanted to take a moment to talk about the themes or topics that have resonated with me the most: big data, machine learning (ML), making the most out of limited resources, threat landscape evaluation, evaluating business risk, ransomware, and IoT threats.
Everyone Wants a Piece of the Big Data Pie
One of the sessions I found particularly interesting was titled, Machine Learning: Cybersecurity Boon or Boondoggle. This session got me thinking about ML—and whether it’s become a buzzword or if it is worth all of the attention it’s been getting. Here are some of my observations as a newbie:
- ML, artificial intelligence (AI), deep learning, and big data are all interrelated. I saw and heard mentions of these buzzwords all over the show floor and it seems they are here to stay because they have applications in Cyber security.
- There are a lot of companies are doing some cool things with technologies leveraging massive data sets. These data sets consist of user, endpoint, network, threat intelligence, historical information on threat actors, and many other sources. But it seems that the successful vendors are applying advanced analytics techniques to this data to provide actionable intelligence to uncover threats, and in some cases, to predict when an attack is happening.
- AI, ML, deep learning, and bid data are not the end-all be-all of analytics. None of the vendors that I saw made claims that their technologies can operate without human intervention. These technologies aren’t the security silver bullet that can be set up and left alone.
- It is important to ensure vendors aren’t setting unrealistic expectations about what these technologies can achieve, including their capabilities and limitations.
- When looking to invest in these advanced technologies, it’s important to do your homework to cut through the hype around these phrases. Any vendor who says “it’s too complicated to understand,” is not being truthful and isn’t worthy of your business. Ask more questions, ask to speak with their data scientists, and go beyond the presented use cases to ensure you fully understand what you’re getting with the product. When you find a vendor who can clearly answer all of your questions and is thrilled to go beyond the basics and the marketing, then you’ll be in good shape.
Look out for another post for me to wrap-up my conference experience. Thanks for reading!
Until next time …